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@string{academic = {Academic Press}}

@string{acmmathsoft = {{ACM} Transactions on Mathematical Software}}

@string{acmpress = {{ACM} Press}}

@string{adamhilger = {Adam Hilger}}

@string{addisonwesley = {Addison-Wesley}}

@string{allynbacon = {Allyn and Bacon}}

@string{amermathmonthly = {American Mathematical Monthly}}

@string{amersocio = {American Journal of Sociology}}

@string{amerstatassoc = {Journal of the American Statistical Association}}

@string{ams = {American Mathematical Society}}

@string{amstrans = {American Mathematical Society Translations}}

@string{applmathcomp = {Applied Mathematics and Computation}}

@string{birkhauser = {Birkha{\"u}ser}}

@string{bit = {{BIT}}}

@string{britstatpsych = {British Journal of Mathematical and Statistical Psychology}}

@string{bullams = {Bulletin of the American Mathematical Society}}

@string{cacm = {Communications of the {ACM}}}

@string{cambridgepress = {Cambridge University Press}}

@string{canmathbull = {Canadian Mathematical Bulletin}}

@string{chelsea = {Chelsea}}

@string{claredonpress = {Claredon Press}}

@string{compapplmath = {Journal of Computational and Applied Mathematics}}

@string{compjour = {The Computer Journal}}

@string{compphys = {Journal of Computational Physics}}

@string{compserv = {Comput. Surveys}}

@string{compstruct = {Computers and Structures}}

@string{compsyssci = {Journal of Computer and System Sciences}}

@string{computer = {{IEEE} Computer}}

@string{computing = {Computing}}

@string{contempmath = {Contemporary Mathematics}}

@string{crelle = {Crelle's Journal}}

@string{doverpub = {Dover Publications}}

@string{eyolles = {Eyolles}}

@string{giornalemath = {Giornale di Mathematiche}}

@string{holtrinehartwinston = {Holt, Rinehart and Winston}}

@string{ieeespec = {{IEEE} Spectrum}}

@string{ieeetransac = {{IEEE} Transactions on Automatic Control}}

@string{ieeetransaeroelec = {{IEEE} Transactions on Aerospace and Electronic Systems}}

@string{ieeetranscomp = {{IEEE} Transactions on Computers}}

@string{imanumerana = {{IMA} Journal of Numerical Analysis}}

@string{infproclet = {Information Processing Letters}}

@string{instmathapp = {Journal of the Institute of Mathematics and its Applications}}

@string{intcontrol = {International Journal of Control}}

@string{interscience = {Interscience}}

@string{intnumereng = {International Journal for Numerical Methods in Engineering}}

@string{intsuper = {International Journal of Supercomputing Applications}}

@string{jacm = {J. ACM}}

@string{johnshopkinspress = {The Johns Hopkins University Press}}

@string{johnwileysons = {John Wiley and Sons}}

@string{jresnatburstand = {Journal of Research of the National Bureau of Standards}}

@string{jsiam = {Journal of the Society for Industrial and Applied Mathematics}}

@string{jsiamb = {Journal of the Society for Industrial and Applied Mathematics, Series B, Numerical Analysis}}

@string{kibernetika = {Kibernetika}}

@string{linalgapp = {Linear Algebra and its Applications}}

@string{macmillan = {Macmillan}}

@string{mathanaappl = {Journal of Mathematical Analysis and Applications}}

@string{mathannalen = {Mathematische Annalen}}

@string{mathcomp = {Mathematics of Computation}}

@string{mathphys = {Journal of Mathematical Physics}}

@string{mathscand = {Mathematica Scandinavica}}

@string{mathworks = {The Math Works Inc.}}

@string{mcgrawhill = {McGraw-Hill}}

@string{natburstd = {National Bureau of Standards}}

@string{northholland = {North-Holland}}

@string{numermath = {Numerische Mathematik}}

@string{oxfordpress = {Oxford University Press}}

@string{pacificmath = {Pacific Journal of Mathematics}}

@string{parcomputing = {Parallel Computing}}

@string{pardistcomp = {Journal of Parallel and Distributed Computing}}

@string{pergamonpress = {Pergamon Press}}

@string{philmag = {Philosophical Magazine}}

@string{plenumpress = {Plenum Press}}

@string{prenticehall = {Prentice-Hall}}

@string{procams = {Proceedings of the American Mathematical Society}}

@string{procieee = {Proceedings of the {IEEE}}}

@string{procnas = {Proceedings of the National Academy of Sciences of the USA}}

@string{psychometrika = {Psychometrika}}

@string{quartapplmath = {Quarterly of Applied Mathematics}}

@string{quartmath = {Quarterly Journal of Mathematics, Oxford, Series (2)}}

@string{revueinststat = {Review of the International Statisical Institute}}

@string{siamalgmeth = {{SIAM} Journal on Algebraic and Discrete Methods}}

@string{siamappmath = {{SIAM} Journal on Applied Mathematics}}

@string{siamcomp = {{SIAM} Journal on Computing}}

@string{siammatrix = {{SIAM} Journal on Matrix Analysis and Applications}}

@string{siamnumanal = {{SIAM} Journal on Numerical Analysis}}

@string{siampub = {{SIAM} Publications}}

@string{siamreview = {{SIAM} Review}}

@string{siamscistat = {{SIAM} Journal on Scientific and Statistical Computing}}

@string{signum = {{ACM} {SIGNUM} Newsletter}}

@string{softpracexp = {Software Practice and Experience}}

@string{springer = {Springer-Verlag}}

@string{statscience = {Statistical Science}}

@string{tablesaidscomp = {Mathematical Tables and Other Aids to Computation}}

@string{techno = {Technometrics}}

@string{texaspress = {University of Texas Press}}

@string{transams = {Transactions of the American Mathematical Society}}

@string{ussrcompmathphys = {{USSR} Computational Mathematics and Mathematical Physics}}

@string{vannostrand = {Van Nostrand}}

@string{vlsicompsys = {Journal of {VLSI} and Computer Systems}}

@string{whfreeman = {W. H. Freeman and Co.}}

@string{zangewmathmech = {Zeitschrift fur Angewandte Mathematik und Mechanik}}

@string{zangewmathphys = {Zeitschrift fur Angewandte Mathematik und Physik}}

@article{Wong2016,
author = {Wong, Wendy S. W. and Solomon, Benjamin D. and Bodian, Dale L. and Kothiyal, Prachi and Eley, Greg and Huddleston, Kathi C. and Baker, Robin and Thach, Dzung C. and Iyer, Ramaswamy K. and Vockley, Joseph G. and Niederhuber, John E.},
doi = {10.1038/ncomms10486},
issn = {2041-1723},
journal = {Nature Communications},
month = {jan},
pages = {10486},
publisher = {Nature Publishing Group},
title = {{New observations on maternal age effect on germline de novo mutations}},
url = {http://www.nature.com/doifinder/10.1038/ncomms10486},
volume = {7},
year = {2016}
}

@article{Ionita-Laza:2016,
	Abstract = {Over the past few years, substantial effort has been put into the functional annotation of variation in human genome sequences. Such annotations can have a critical role in identifying putatively causal variants for a disease or trait among the abundant natural variation that occurs at a locus of interest. The main challenges in using these various annotations include their large numbers and their diversity. Here we develop an unsupervised approach to integrate these different annotations into one measure of functional importance (Eigen) that, unlike most existing methods, is not based on any labeled training data. We show that the resulting meta-score has better discriminatory ability using disease-associated and putatively benign variants from published studies (in both coding and noncoding regions) than the recently proposed CADD score. Across varied scenarios, the Eigen score performs generally better than any single individual annotation, representing a powerful single functional score that can be incorporated in fine-mapping studies.},
	Author = {Ionita-Laza, Iuliana and McCallum, Kenneth and Xu, Bin and Buxbaum, Joseph D},
	Date-Added = {2016-02-08 17:08:07 +0000},
	Date-Modified = {2016-02-08 17:08:07 +0000},
	Doi = {10.1038/ng.3477},
	Journal = {Nat Genet},
	Journal-Full = {Nature genetics},
	Month = {Feb},
	Number = {2},
	Pages = {214-20},
	Pmc = {PMC4731313},
	Pmid = {26727659},
	Pst = {ppublish},
	Title = {A spectral approach integrating functional genomic annotations for coding and noncoding variants},
	Volume = {48},
	Year = {2016},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/ng.3477}}

@article{deLigt2012,
	Abstract = {The causes of intellectual disability remain largely unknown because
	of extensive clinical and genetic heterogeneity.We evaluated patients
	with intellectual disability to exclude known causes of the disorder.
	We then sequenced the coding regions of more than 21,000 genes obtained
	from 100 patients with an IQ below 50 and their unaffected parents.
	A data-analysis procedure was developed to identify and classify
	de novo, autosomal recessive, and X-linked mutations. In addition,
	we used high-throughput resequencing to confirm new candidate genes
	in 765 persons with intellectual disability (a confirmation series).
	All mutations were evaluated by molecular geneticists and clinicians
	in the context of the patients' clinical presentation.We identified
	79 de novo mutations in 53 of 100 patients. A total of 10 de novo
	mutations and 3 X-linked (maternally inherited) mutations that had
	been previously predicted to compromise the function of known intellectual-disability
	genes were found in 13 patients. Potentially causative de novo mutations
	in novel candidate genes were detected in 22 patients. Additional
	de novo mutations in 3 of these candidate genes were identified in
	patients with similar phenotypes in the confirmation series, providing
	support for mutations in these genes as the cause of intellectual
	disability. We detected no causative autosomal recessive inherited
	mutations in the discovery series. Thus, the total diagnostic yield
	was 16\%, mostly involving de novo mutations.De novo mutations represent
	an important cause of intellectual disability; exome sequencing was
	used as an effective diagnostic strategy for their detection. (Funded
	by the European Union and others.).},
	Author = {{de Ligt}, Joep and Willemsen, Marjolein H. and {van Bon}, Bregje W M. and Kleefstra, Tjitske and Yntema, Helger G. and Kroes, Thessa and {Vulto-van Silfhout}, Anneke T. and Koolen, David A. and {de Vries}, Petra and Gilissen, Christian and {del Rosario}, Marisol and Hoischen, Alexander and Scheffer, Hans and {de Vries}, Bert B A. and Brunner, Han G. and Veltman, Joris A. and Vissers, Lisenka E L M.},
	Doi = {10.1056/NEJMoa1206524},
	Institution = {Department of Human Genetics, Institute for Genetic and Metabolic Disease, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands.},
	Journal = {N Engl J Med},
	Keywords = {Adolescent; Child; Exome, genetics; Female; Genes, Recessive, genetics; Genes, X-Linked; Genetic Diseases, X-Linked, genetics; Humans; Intellectual Disability, genetics; Male; Mutation; Sequence Analysis, DNA; Young Adult},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Nov},
	Number = {20},
	Owner = {peter},
	Pages = {1921--1929},
	Pmid = {23033978},
	Timestamp = {2015.08.09},
	Title = {Diagnostic exome sequencing in persons with severe intellectual disability.},
	Url = {http://dx.doi.org/10.1056/NEJMoa1206524},
	Volume = {367},
	Year = {2012},
	Bdsk-Url-1 = {http://dx.doi.org/10.1056/NEJMoa1206524}}

@article{deVooght2009,
	Abstract = {Although promoter mutations are known to cause functionally important
	consequences for gene expression, promoter analysis is not a regular
	part of DNA diagnostics.This review covers different important aspects
	of promoter mutation analysis and includes a proposed model procedure
	for studying promoter mutations. Characterization of a promoter sequence
	variation includes a comprehensive study of the literature and databases
	of human mutations and transcription factors. Phylogenetic footprinting
	is also used to evaluate the putative importance of the promoter
	region of interest. This in silico analysis is, in general, followed
	by in vitro functional assays, of which transient and stable transfection
	assays are considered the gold-standard methods. Electrophoretic
	mobility shift and supershift assays are used to identify trans-acting
	proteins that putatively interact with the promoter region of interest.
	Finally, chromatin immunoprecipitation assays are essential to confirm
	in vivo binding of these proteins to the promoter.Although promoter
	mutation analysis is complex, often laborious, and difficult to perform,
	it is an essential part of the diagnosis of disease-causing promoter
	mutations and improves our understanding of the role of transcriptional
	regulation in human disease. We recommend that routine laboratories
	and research groups specialized in gene promoter research cooperate
	to expand general knowledge and diagnosis of gene-promoter defects.},
	Author = {{de Vooght}, Karen M K. and {van Wijk}, Richard and {van Solinge}, Wouter W.},
	Doi = {10.1373/clinchem.2008.120931},
	Institution = {Department of Clinical Chemistry and Haematology, Laboratory for Red Blood Cell Research, University Medical Center Utrecht, Utrecht, the Netherlands. k.devooght@umcutrecht.nl},
	Journal = {Clin Chem},
	Keywords = {Animals; Computational Biology; Disease; Humans; Molecular Diagnostic Techniques, methods; Mutation, genetics; Promoter Regions, Genetic, genetics; Sequence Analysis, DNA},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Apr},
	Number = {4},
	Owner = {peter},
	Pages = {698--708},
	Pii = {clinchem.2008.120931},
	Pmid = {19246615},
	Timestamp = {2015.07.18},
	Title = {Management of gene promoter mutations in molecular diagnostics.},
	Url = {http://dx.doi.org/10.1373/clinchem.2008.120931},
	Volume = {55},
	Year = {2009},
	Bdsk-Url-1 = {http://dx.doi.org/10.1373/clinchem.2008.120931}}

@article{DeLong88,
	Author = {"DeLong, E.R. and DeLong, D.M. and Clarke-Pearson, D.L."},
	Journal = {Biometrics},
	Number = {3},
	Pages = {pp. 837-845},
	Publisher = {International Biometric Society},
	Title = {Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach},
	Url = {http://www.jstor.org/stable/2531595},
	Volume = {44},
	Year = {1988},
	Bdsk-Url-1 = {http://www.jstor.org/stable/2531595}}

@article{thousandGenomes2010,
	Abstract = {The 1000 Genomes Project aims to provide a deep characterization of
	human genome sequence variation as a foundation for investigating
	the relationship between genotype and phenotype. Here we present
	results of the pilot phase of the project, designed to develop and
	compare different strategies for genome-wide sequencing with high-throughput
	platforms. We undertook three projects: low-coverage whole-genome
	sequencing of 179 individuals from four populations; high-coverage
	sequencing of two mother-father-child trios; and exon-targeted sequencing
	of 697 individuals from seven populations. We describe the location,
	allele frequency and local haplotype structure of approximately 15
	million single nucleotide polymorphisms, 1 million short insertions
	and deletions, and 20,000 structural variants, most of which were
	previously undescribed. We show that, because we have catalogued
	the vast majority of common variation, over 95\% of the currently
	accessible variants found in any individual are present in this data
	set. On average, each person is found to carry approximately 250
	to 300 loss-of-function variants in annotated genes and 50 to 100
	variants previously implicated in inherited disorders. We demonstrate
	how these results can be used to inform association and functional
	studies. From the two trios, we directly estimate the rate of de
	novo germline base substitution mutations to be approximately 10(-8)
	per base pair per generation. We explore the data with regard to
	signatures of natural selection, and identify a marked reduction
	of genetic variation in the neighbourhood of genes, due to selection
	at linked sites. These methods and public data will support the next
	phase of human genetic research.},
	Author = {{1000 Genomes Project Consortium} and Abecasis, Gon{\c{c}}alo R. and Altshuler, David and Auton, Adam and Brooks, Lisa D. and Durbin, Richard M. and Gibbs, Richard A. and Hurles, Matt E. and McVean, Gil A.},
	Doi = {10.1038/nature09534},
	Journal = {Nature},
	Keywords = {Calibration; Chromosomes, Human, Y, genetics; Computational Biology; DNA Mutational Analysis; DNA, Mitochondrial, genetics; Evolution, Molecular; Female; Genetic Association Studies; Genetic Variation, genetics; Genetics, Population, methods; Genome, Human, genetics; Genome-Wide Association Study; Genomics, methods; Genotype; Haplotypes, genetics; Humans; Male; Mutation, genetics; Pilot Projects; Polymorphism, Single Nucleotide, genetics; Recombination, Genetic, genetics; Sample Size; Selection, Genetic, genetics; Sequence Alignment; Sequence Analysis, DNA, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Oct},
	Number = {7319},
	Owner = {peter},
	Pages = {1061--1073},
	Pii = {nature09534},
	Pmid = {20981092},
	Timestamp = {2015.05.30},
	Title = {A map of human genome variation from population-scale sequencing.},
	Url = {http://dx.doi.org/10.1038/nature09534},
	Volume = {467},
	Year = {2010},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nature09534}}

@article{Abecasis2012,
	Abstract = {By characterizing the geographic and functional spectrum of human
	genetic variation, the 1000 Genomes Project aims to build a resource
	to help to understand the genetic contribution to disease. Here we
	describe the genomes of 1,092 individuals from 14 populations, constructed
	using a combination of low-coverage whole-genome and exome sequencing.
	By developing methods to integrate information across several algorithms
	and diverse data sources, we provide a validated haplotype map of
	38 million single nucleotide polymorphisms, 1.4 million short
	insertions and deletions, and more than 14,000 larger deletions.
	We show that individuals from different populations carry different
	profiles of rare and common variants, and that low-frequency variants
	show substantial geographic differentiation, which is further increased
	by the action of purifying selection. We show that evolutionary conservation
	and coding consequence are key determinants of the strength of purifying
	selection, that rare-variant load varies substantially across biological
	pathways, and that each individual contains hundreds of rare non-coding
	variants at conserved sites, such as motif-disrupting changes in
	transcription-factor-binding sites. This resource, which captures
	up to 98\% of accessible single nucleotide polymorphisms at a frequency
	of 1\% in related populations, enables analysis of common and low-frequency
	variants in individuals from diverse, including admixed, populations.},
	Author = {Abecasis, Goncalo R and Auton, Adam and Brooks, Lisa D and DePristo, Mark A and Durbin, Richard M and Handsaker, Robert E and Kang, Hyun Min and Marth, Gabor T and McVean, Gil A},
	Doi = {10.1038/nature11632},
	Issn = {1476-4687},
	Journal = {Nature},
	Keywords = {Alleles,Binding Sites,Binding Sites: genetics,Conserved Sequence,Conserved Sequence: genetics,Continental Population Groups,Continental Population Groups: genetics,Evolution, Molecular,Genetic Variation,Genetic Variation: genetics,Genetics, Medical,Genetics, Population,Genome, Human,Genome, Human: genetics,Genome-Wide Association Study,Genomics,Haplotypes,Haplotypes: genetics,Humans,Nucleotide Motifs,Polymorphism, Single Nucleotide,Polymorphism, Single Nucleotide: genetics,Sequence Deletion,Sequence Deletion: genetics,Transcription Factors,Transcription Factors: metabolism},
	Mendeley-Groups = {Bioinformatic/Genomiser},
	Month = nov,
	Number = {7422},
	Pages = {56--65},
	Pmid = {23128226},
	Publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
	Shorttitle = {Nature},
	Title = {{An integrated map of genetic variation from 1,092 human genomes.}},
	Url = {http://dx.doi.org/10.1038/nature11632},
	Volume = {491},
	Year = {2012},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nature11632}}

@article{Adzhubei2010,
	Author = {Adzhubei, Ivan A. and Schmidt, Steffen and Peshkin, Leonid and Ramensky, Vasily E. and Gerasimova, Anna and Bork, Peer and Kondrashov, Alexey S. and Sunyaev, Shamil R.},
	Doi = {10.1038/nmeth0410-248},
	Journal = {Nat Methods},
	Keywords = {Data Interpretation, Statistical; Genetic Variation; Humans; Models, Genetic; Mutation, Missense; Software},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Apr},
	Number = {4},
	Owner = {peter},
	Pages = {248--249},
	Pii = {nmeth0410-248},
	Pmid = {20354512},
	Timestamp = {2015.08.05},
	Title = {A method and server for predicting damaging missense mutations.},
	Url = {http://dx.doi.org/10.1038/nmeth0410-248},
	Volume = {7},
	Year = {2010},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nmeth0410-248}}

@article{Ahituv2007,
	Abstract = {Ultraconserved elements have been suggested to retain extended perfect
	sequence identity between the human, mouse, and rat genomes due to
	essential functional properties. To investigate the necessities of
	these elements in vivo, we removed four noncoding ultraconserved
	elements (ranging in length from 222 to 731 base pairs) from the
	mouse genome. To maximize the likelihood of observing a phenotype,
	we chose to delete elements that function as enhancers in a mouse
	transgenic assay and that are near genes that exhibit marked phenotypes
	both when completely inactivated in the mouse and when their expression
	is altered due to other genomic modifications. Remarkably, all four
	resulting lines of mice lacking these ultraconserved elements were
	viable and fertile, and failed to reveal any critical abnormalities
	when assayed for a variety of phenotypes including growth, longevity,
	pathology, and metabolism. In addition, more targeted screens, informed
	by the abnormalities observed in mice in which genes in proximity
	to the investigated elements had been altered, also failed to reveal
	notable abnormalities. These results, while not inclusive of all
	the possible phenotypic impact of the deleted sequences, indicate
	that extreme sequence constraint does not necessarily reflect crucial
	functions required for viability.},
	Author = {Ahituv, Nadav and Zhu, Yiwen and Visel, Axel and Holt, Amy and Afzal, Veena and Pennacchio, Len A. and Rubin, Edward M.},
	Doi = {10.1371/journal.pbio.0050234},
	Institution = {Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America.},
	Journal = {PLoS Biol},
	Keywords = {Animals; Conserved Sequence, physiology; Fertility; Genome; Mice; Phenotype; Sequence Deletion, physiology; Survival},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Sep},
	Number = {9},
	Owner = {peter},
	Pages = {e234},
	Pii = {07-PLBI-RA-1373},
	Pmid = {17803355},
	Timestamp = {2015.08.09},
	Title = {Deletion of ultraconserved elements yields viable mice.},
	Url = {http://dx.doi.org/10.1371/journal.pbio.0050234},
	Volume = {5},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1371/journal.pbio.0050234}}

@article{Andersson2014,
	Abstract = {Enhancers control the correct temporal and cell-type-specific activation
	of gene expression in multicellular eukaryotes. Knowing their properties,
	regulatory activity and targets is crucial to understand the regulation
	of differentiation and homeostasis. Here we use the FANTOM5 panel
	of samples, covering the majority of human tissues and cell types,
	to produce an atlas of active, in vivo-transcribed enhancers. We
	show that enhancers share properties with CpG-poor messenger RNA
	promoters but produce bidirectional, exosome-sensitive, relatively
	short unspliced RNAs, the generation of which is strongly related
	to enhancer activity. The atlas is used to compare regulatory programs
	between different cells at unprecedented depth, to identify disease-associated
	regulatory single nucleotide polymorphisms, and to classify cell-type-specific
	and ubiquitous enhancers. We further explore the utility of enhancer
	redundancy, which explains gene expression strength rather than expression
	patterns. The online FANTOM5 enhancer atlas represents a unique resource
	for studies on cell-type-specific enhancers and gene regulation.},
	Author = {Andersson, Robin and Gebhard, Claudia and Miguel-Escalada, Irene and Hoof, Ilka and Bornholdt, Jette and Boyd, Mette and Chen, Yun and Zhao, Xiaobei and Schmidl, Christian and Suzuki, Takahiro and Ntini, Evgenia and Arner, Erik and Valen, Eivind and Li, Kang and Schwarzfischer, Lucia and Glatz, Dagmar and Raithel, Johanna and Lilje, Berit and Rapin, Nicolas and Bagger, Frederik Otzen and J{\o}rgensen, Mette and Andersen, Peter Refsing and Bertin, Nicolas and Rackham, Owen and Burroughs, A Maxwell and Baillie, J Kenneth and Ishizu, Yuri and Shimizu, Yuri and Furuhata, Erina and Maeda, Shiori and Negishi, Yutaka and Mungall, Christopher J. and Meehan, Terrence F. and Lassmann, Timo and Itoh, Masayoshi and Kawaji, Hideya and Kondo, Naoto and Kawai, Jun and Lennartsson, Andreas and Daub, Carsten O. and Heutink, Peter and Hume, David A. and Jensen, Torben Heick and Suzuki, Harukazu and Hayashizaki, Yoshihide and M{\"u}ller, Ferenc and , F. A. N. T. O. M Consortium and Forrest, Alistair R R. and Carninci, Piero and Rehli, Michael and Sandelin, Albin},
	Doi = {10.1038/nature12787},
	Institution = {Biotech Research and Innovation Centre, University of Copenhagen, Ole Maaloes Vej 5, DK-2200 Copenhagen, Denmark.},
	Journal = {Nature},
	Keywords = {Atlases as Topic; Cell Line; Cells, Cultured; Cluster Analysis; Enhancer Elements, Genetic, genetics; Gene Expression Regulation, genetics; Genetic Predisposition to Disease, genetics; HeLa Cells; Humans; Molecular Sequence Annotation; Organ Specificity; Polymorphism, Single Nucleotide, genetics; Promoter Regions, Genetic, genetics; RNA, Messenger, biosynthesis/genetics; Transcription Initiation Site; Transcription Initiation, Genetic},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Mar},
	Number = {7493},
	Owner = {peter},
	Pages = {455--461},
	Pii = {nature12787},
	Pmid = {24670763},
	Timestamp = {2015.06.13},
	Title = {An atlas of active enhancers across human cell types and tissues.},
	Url = {http://dx.doi.org/10.1038/nature12787},
	Volume = {507},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nature12787}}

@article{Barbosa2013,
	Abstract = {Upstream open reading frames (uORFs) are major gene expression regulatory
	elements. In many eukaryotic mRNAs, one or more uORFs precede the
	initiation codon of the main coding region. Indeed, several studies
	have revealed that almost half of human transcripts present uORFs.
	Very interesting examples have shown that these uORFs can impact
	gene expression of the downstream main ORF by triggering mRNA decay
	or by regulating translation. Also, evidence from recent genetic
	and bioinformatic studies implicates disturbed uORF-mediated translational
	control in the etiology of many human diseases, including malignancies,
	metabolic or neurologic disorders, and inherited syndromes. In this
	review, we will briefly present the mechanisms through which uORFs
	regulate gene expression and how they can impact on the organism's
	response to different cell stress conditions. Then, we will emphasize
	the importance of these structures by illustrating, with specific
	examples, how disturbed uORF-mediated translational control can be
	involved in the etiology of human diseases, giving special importance
	to genotype-phenotype correlations. Identifying and studying more
	cases of uORF-altering mutations will help us to understand and establish
	genotype-phenotype associations, leading to advancements in diagnosis,
	prognosis, and treatment of many human disorders.},
	Author = {Barbosa, Cristina and Peixeiro, Isabel and Rom{\~{a}}o, Lu{\'{i}}sa},
	Doi = {10.1371/journal.pgen.1003529},
	Institution = {Departamento de Gen{\'e}tica Humana, Instituto Nacional de Sa{\'u}de Dr. Ricardo Jorge, Lisboa, Portugal.},
	Journal = {PLoS Genet},
	Keywords = {5' Untranslated Regions, genetics; Disease, genetics; Gene Expression Regulation; Genetic Association Studies; Humans; Mutation; Open Reading Frames, genetics; Protein Biosynthesis, genetics; RNA Stability; Regulatory Sequences, Nucleic Acid, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Number = {8},
	Owner = {peter},
	Pages = {e1003529},
	Pii = {PGENETICS-D-13-00138},
	Pmid = {23950723},
	Timestamp = {2015.07.18},
	Title = {Gene expression regulation by upstream open reading frames and human disease.},
	Url = {http://dx.doi.org/10.1371/journal.pgen.1003529},
	Volume = {9},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1371/journal.pgen.1003529}}

@article{Barolo2012,
	Abstract = {This paper, in the form of a frequently asked questions page (FAQ),
	addresses outstanding questions about "shadow enhancers", quasi-redundant
	cis-regulatory elements, and their proposed roles in transcriptional
	control. Questions include: What exactly are shadow enhancers? How
	many genes have shadow/redundant/distributed enhancers? How redundant
	are these elements? What is the function of distributed enhancers?
	How modular are enhancers? Is it useful to study a single enhancer
	in isolation? In addition, a revised definition of "shadow enhancers"
	is proposed, and possible mechanisms of shadow enhancer function
	and evolution are discussed.},
	Author = {Barolo, Scott},
	Doi = {10.1002/bies.201100121},
	Institution = {Department of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI, USA. sbarolo@umich.edu},
	Journal = {Bioessays},
	Keywords = {Enhancer Elements, Genetic; Gene Expression Regulation; Genomics; Humans; Transcription, Genetic},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Feb},
	Number = {2},
	Owner = {peter},
	Pages = {135--141},
	Pmid = {22083793},
	Timestamp = {2015.08.09},
	Title = {Shadow enhancers: frequently asked questions about distributed cis-regulatory information and enhancer redundancy.},
	Url = {http://dx.doi.org/10.1002/bies.201100121},
	Volume = {34},
	Year = {2012},
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/bies.201100121}}

@article{Beck2014,
	Abstract = {To facilitate broad and convenient integrative visualization of and
	access to GWAS data, we have created the GWAS Central resource (http://www.gwascentral.org).
	This database seeks to provide a comprehensive collection of summary-level
	genetic association data, structured both for maximal utility and
	for safe open access (i.e., non-directional signals to fully preclude
	research subject identification). The resource emphasizes on advanced
	tools that allow comparison and discovery of relevant data sets from
	the perspective of genes, genome regions, phenotypes or traits. Tested
	markers and relevant genomic features can be visually interrogated
	across up to 16 multiple association data sets in a single view,
	starting at a chromosome-wide view and increasing in resolution down
	to individual bases. In addition, users can privately upload and
	view their own data as temporary files. Search and display utility
	is further enhanced by exploiting phenotype ontology annotations
	to allow genetic variants associated with phenotypes and traits of
	interest to be precisely identified, across all studies. Data submissions
	are accepted from individual researchers, groups and consortia, whereas
	we also actively gather data sets from various public sources. As
	a result, the resource now provides over 67 million P-values for
	over 1600 studies, making it the world's largest openly accessible
	online collection of summary-level GWAS association information.},
	Author = {Beck, Tim and Hastings, Robert K. and Gollapudi, Sirisha and Free, Robert C. and Brookes, Anthony J.},
	Doi = {10.1038/ejhg.2013.274},
	Institution = {Department of Genetics, University of Leicester, Leicester, UK.},
	Journal = {Eur J Hum Genet},
	Keywords = {Databases, Genetic; Female; Genome, Human; Genome-Wide Association Study; Humans; Internet; Male; Quantitative Trait, Heritable},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jul},
	Number = {7},
	Owner = {peter},
	Pages = {949--952},
	Pii = {ejhg2013274},
	Pmid = {24301061},
	Timestamp = {2015.08.09},
	Title = {GWAS Central: a comprehensive resource for the comparison and interrogation of genome-wide association studies.},
	Url = {http://dx.doi.org/10.1038/ejhg.2013.274},
	Volume = {22},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/ejhg.2013.274}}

@article{Bell2011,
	Abstract = {Of 7028 disorders with suspected Mendelian inheritance, 1139 are recessive
	and have an established molecular basis. Although individually uncommon,
	Mendelian diseases collectively account for ~20\% of infant mortality
	and ~10\% of pediatric hospitalizations. Preconception screening,
	together with genetic counseling of carriers, has resulted in remarkable
	declines in the incidence of several severe recessive diseases including
	Tay-Sachs disease and cystic fibrosis. However, extension of preconception
	screening to most severe disease genes has hitherto been impractical.
	Here, we report a preconception carrier screen for 448 severe recessive
	childhood diseases. Rather than costly, complete sequencing of the
	human genome, 7717 regions from 437 target genes were enriched by
	hybrid capture or microdroplet polymerase chain reaction, sequenced
	by next-generation sequencing (NGS) to a depth of up to 2.7 gigabases,
	and assessed with stringent bioinformatic filters. At a resultant
	160x average target coverage, 93\% of nucleotides had at least 20x
	coverage, and mutation detection/genotyping had ~95\% sensitivity
	and ~100\% specificity for substitution, insertion/deletion, splicing,
	and gross deletion mutations and single-nucleotide polymorphisms.
	In 104 unrelated DNA samples, the average genomic carrier burden
	for severe pediatric recessive mutations was 2.8 and ranged from
	0 to 7. The distribution of mutations among sequenced samples appeared
	random. Twenty-seven percent of mutations cited in the literature
	were found to be common polymorphisms or misannotated, underscoring
	the need for better mutation databases as part of a comprehensive
	carrier testing strategy. Given the magnitude of carrier burden and
	the lower cost of testing compared to treating these conditions,
	carrier screening by NGS made available to the general population
	may be an economical way to reduce the incidence of and ameliorate
	suffering associated with severe recessive childhood disorders.},
	Author = {Bell, Callum J. and Dinwiddie, Darrell L. and Miller, Neil A. and Hateley, Shannon L. and Ganusova, Elena E. and Mudge, Joann and Langley, Ray J. and Zhang, Lu and Lee, Clarence C. and Schilkey, Faye D. and Sheth, Vrunda and Woodward, Jimmy E. and Peckham, Heather E. and Schroth, Gary P. and Kim, Ryan W. and Kingsmore, Stephen F.},
	Doi = {10.1126/scitranslmed.3001756},
	Institution = {National Center for Genome Resources, Santa Fe, NM 87505, USA.},
	Journal = {Sci Transl Med},
	Keywords = {Base Sequence; Child; Databases, Genetic; Female; Genes, Recessive, genetics; Genetic Testing, economics/methods; Genome, Human; Heterozygote; Heterozygote Detection, methods; Humans; Molecular Sequence Data; Mutation; Pregnancy; Prenatal Diagnosis; Sequence Alignment; Sequence Analysis, DNA, economics/methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {65},
	Owner = {peter},
	Pages = {65ra4},
	Pii = {3/65/65ra4},
	Pmid = {21228398},
	Timestamp = {2015.08.09},
	Title = {Carrier testing for severe childhood recessive diseases by next-generation sequencing.},
	Url = {http://dx.doi.org/10.1126/scitranslmed.3001756},
	Volume = {3},
	Year = {2011},
	Bdsk-Url-1 = {http://dx.doi.org/10.1126/scitranslmed.3001756}}

@book{Bis95,
	Address = {Oxford},
	Author = {Bishop, C. M.},
	Publisher = {Clarendon Press},
	Title = {Neural Networks for Pattern Recognition},
	Year = {1995}}

@article{Breiman,
	Author = {Breiman, Leo},
	Date-Added = {2015-09-22 17:31:22 +0000},
	Date-Modified = {2015-09-22 17:31:42 +0000},
	Journal = {Machine Learning},
	Number = {1},
	Pages = {5--32},
	Publisher = {Springer},
	Title = {Random forests},
	Volume = {45},
	Year = {2001}}

@book{Bre84,
	Address = {Belmont, CA},
	Author = {Breiman, L. and Friedman, G.H. and Olshen, R.A. and Stone, C.J.},
	Publisher = {Wadsworth},
	Title = {Classification And Regression Trees},
	Year = {1984}}

@article{Calvo2009,
	Abstract = {Upstream ORFs (uORFs) are mRNA elements defined by a start codon in
	the 5' UTR that is out-of-frame with the main coding sequence. Although
	uORFs are present in approximately half of human and mouse transcripts,
	no study has investigated their global impact on protein expression.
	Here, we report that uORFs correlate with significantly reduced protein
	expression of the downstream ORF, based on analysis of 11,649 matched
	mRNA and protein measurements from 4 published mammalian studies.
	Using reporter constructs to test 25 selected uORFs, we estimate
	that uORFs typically reduce protein expression by 30-80\%, with a
	modest impact on mRNA levels. We additionally identify polymorphisms
	that alter uORF presence in 509 human genes. Finally, we report that
	5 uORF-altering mutations, detected within genes previously linked
	to human diseases, dramatically silence expression of the downstream
	protein. Together, our results suggest that uORFs influence the protein
	expression of thousands of mammalian genes and that variation in
	these elements can influence human phenotype and disease.},
	Author = {Calvo, Sarah E. and Pagliarini, David J. and Mootha, Vamsi K.},
	Doi = {10.1073/pnas.0810916106},
	Institution = {Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.},
	Journal = {Proc Natl Acad Sci U S A},
	Keywords = {5' Untranslated Regions, genetics; Base Sequence; Disease, genetics; Humans; Molecular Sequence Data; Mutation; Open Reading Frames; Polymorphism, Genetic; Protein Biosynthesis, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {May},
	Number = {18},
	Owner = {peter},
	Pages = {7507--7512},
	Pii = {0810916106},
	Pmid = {19372376},
	Timestamp = {2015.07.18},
	Title = {Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans.},
	Url = {http://dx.doi.org/10.1073/pnas.0810916106},
	Volume = {106},
	Year = {2009},
	Bdsk-Url-1 = {http://dx.doi.org/10.1073/pnas.0810916106}}

@article{Cammaerts2015,
	Abstract = {MicroRNAs (miRNAs) are important regulators of gene expression and
	like any other gene, their coding sequences are subject to genetic
	variation. Variants in miRNA genes can have profound effects on miRNA
	functionality at all levels, including miRNA transcription, maturation,
	and target specificity, and as such they can also contribute to disease.
	The impact of variants in miRNA genes is the focus of the present
	review. To put these effects into context, we first discuss the requirements
	of miRNA transcripts for maturation. In the last part an overview
	of available databases and tools and experimental approaches to investigate
	miRNA variants related to human disease is presented.},
	Author = {Cammaerts, Sophia and Strazisar, Mojca and {De Rijk}, Peter and {Del Favero}, Jurgen},
	Doi = {10.3389/fgene.2015.00186},
	Institution = {, University of Antwerp Antwerp, Belgium ; Multiplicom N.V., Niel Belgium.},
	Journal = {Front Genet},
	Language = {eng},
	Medline-Pst = {epublish},
	Owner = {peter},
	Pages = {186},
	Pmid = {26052338},
	Timestamp = {2015.08.09},
	Title = {Genetic variants in {microRNA} genes: impact on {microRNA} expression, function, and disease.},
	Url = {http://dx.doi.org/10.3389/fgene.2015.00186},
	Volume = {6},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.3389/fgene.2015.00186}}

@article{Cazzola2000,
	Abstract = {In higher eukaryotes, the expression of about 1 gene in 10 is strongly
	regulated at the level of messenger RNA (mRNA) translation into protein.
	Negative regulatory effects are often mediated by the 5'-untranslated
	region (5'-UTR) and rely on the fact that the 40S ribosomal subunit
	first binds to the cap structure at the 5'-end of mRNA and then scans
	for the first AUG codon. Self-complementary sequences can form stable
	stem-loop structures that interfere with the assembly of the preinitiation
	complex and/or ribosomal scanning. These stem loops can be further
	stabilized by the interaction with RNA-binding proteins, as in the
	case of ferritin. The presence of AUG codons located upstream of
	the physiological start site can inhibit translation by causing premature
	initiation and thereby preventing the ribosome from reaching the
	physiological start codon, as in the case of thrombopoietin (TPO).
	Recently, mutations that cause disease through increased or decreased
	efficiency of mRNA translation have been discovered, defining translational
	pathophysiology as a novel mechanism of human disease. Hereditary
	hyperferritinemia/cataract syndrome arises from various point mutations
	or deletions within a protein-binding sequence in the 5'-UTR of the
	L-ferritin mRNA. Each unique mutation confers a characteristic degree
	of hyperferritinemia and severity of cataract in affected individuals.
	Hereditary thrombocythemia (sometimes called familial essential thrombocythemia
	or familial thrombocytosis) can be caused by mutations in upstream
	AUG codons in the 5'-UTR of the TPO mRNA that normally function as
	translational repressors. Their inactivation leads to excessive production
	of TPO and elevated platelet counts. Finally, predisposition to melanoma
	may originate from mutations that create translational repressors
	in the 5'-UTR of the cyclin-dependent kinase inhibitor-2A gene.},
	Author = {Cazzola, M. and Skoda, R. C.},
	Institution = {Department of Hematology, University of Pavia Medical School and Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Policlinico S. Matteo, Pavia, Italy.},
	Journal = {Blood},
	Keywords = {5' Untranslated Regions, genetics; Base Sequence; Ferritins, genetics; Genetic Diseases, Inborn, genetics/physiopathology; Genetics, Medical; Humans; Molecular Sequence Data; Nucleic Acid Conformation; Protein Biosynthesis; RNA, Messenger, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jun},
	Number = {11},
	Owner = {peter},
	Pages = {3280--3288},
	Pmid = {10828006},
	Timestamp = {2015.08.06},
	Title = {Translational pathophysiology: a novel molecular mechanism of human disease.},
	Volume = {95},
	Year = {2000}}

@article{Cessie1992,
	Author = {Cessie, S Le and Houwelingen, JC Van},
	Journal = {Applied statistics},
	Title = {{Ridge estimators in logistic regression}},
	Url = {http://www.jstor.org/stable/2347628},
	Year = {1992},
	Bdsk-Url-1 = {http://www.jstor.org/stable/2347628}}

@article{Chatterjee2009,
	Abstract = {Protein synthesis is often regulated at the level of initiation of
	translation, making it a critical step. This regulation occurs by
	both the cis-regulatory elements, which are located in the 5'- and
	3'-UTRs (untranslated regions), and trans-acting factors. A breakdown
	in this regulation machinery can perturb cellular metabolism, leading
	to various physiological abnormalities. The highly structured UTRs,
	along with features such as GC-richness, upstream open reading frames
	and internal ribosome entry sites, significantly influence the rate
	of translation of mRNAs. In this review, we discuss how changes in
	the cis-regulatory sequences of the UTRs, for example, point mutations
	and truncations, influence expression of specific genes at the level
	of translation. Such modifications may tilt the physiological balance
	from healthy to diseased states, resulting in conditions such as
	hereditary thrombocythaemia, breast cancer, fragile X syndrome, bipolar
	affective disorder and Alzheimer's disease. This information tends
	to establish the crucial role of UTRs, perhaps as much as that of
	coding sequences, in health and disease.},
	Author = {Chatterjee, Sangeeta and Pal, Jayanta K.},
	Doi = {10.1042/BC20080104},
	Institution = {Cell and Molecular Biology Laboratory, Department of Biotechnology, University of Pune, Pune 411007, India. jkpal@unipune.ernet.in},
	Journal = {Biol Cell},
	Keywords = {3' Untranslated Regions; 5' Untranslated Regions; Disease, genetics; Humans; Mutation; Open Reading Frames; Polyadenylation; RNA, Messenger, genetics/metabolism; RNA-Binding Proteins, metabolism},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {May},
	Number = {5},
	Owner = {peter},
	Pages = {251--262},
	Pii = {BC20080104},
	Pmid = {19275763},
	Timestamp = {2015.07.17},
	Title = {Role of 5'- and 3'-untranslated regions of {mRNAs} in human diseases.},
	Url = {http://dx.doi.org/10.1042/BC20080104},
	Volume = {101},
	Year = {2009},
	Bdsk-Url-1 = {http://dx.doi.org/10.1042/BC20080104}}

@article{Chawla2002,
	Author = {Chawla, N. V. and Bowyer, K. W. and Hall, L. O. and Kegelmeyer, W. P.},
	Journal = {Journal of Artificial Intelligence Research},
	Mendeley-Groups = {Bioinformatic/Genomiser},
	Pages = {321--357},
	Title = {{SMOTE: Synthetic Minority Over-sampling Technique}},
	Url = {http://www.jair.org/papers/paper953.html},
	Year = {2002},
	Bdsk-Url-1 = {http://www.jair.org/papers/paper953.html}}

@article{Chen2006,
	Abstract = {The 3' regulatory regions (3' RRs) of human genes play an important
	role in regulating mRNA 3' end formation, stability/degradation,
	nuclear export, subcellular localization and translation and are
	consequently rich in regulatory elements. Although 3' RRs contain
	only approximately 0.2\% of known disease-associated mutations, this
	is likely to represent a rather conservative estimate of their actual
	prevalence. In an attempt to catalogue 3' RR-mediated disease and
	also to gain a greater understanding of the functional role of regulatory
	elements within 3' RRs, we have performed a systematic analysis of
	disease-associated 3' RR variants; 121 3' RR variants in 94 human
	genes were collated. These included 17 mutations in the upstream
	core polyadenylation signal sequence (UCPAS), 81 in the upstream
	sequence (USS) between the translational termination codon and the
	UCPAS, 6 in the left arm of the 'spacer' sequence (LAS) between the
	UCPAS and the pre-mRNA cleavage site (CS), 3 in the right arm of
	the 'spacer' sequence (RAS) or downstream core polyadenylation signal
	sequence (DCPAS) and 7 in the downstream sequence (DSS) of the 3'-flanking
	region, with 7 further mutations being treated as isolated examples.
	All the UCPAS mutations and the rather unusual cases of the DMPK,
	SCA8, FCMD and GLA mutations exert a significant effect on the mRNA
	phenotype and are usually associated with monogenic disease. By contrast,
	most of the remaining variants are polymorphisms that exert a comparatively
	minor influence on mRNA expression, but which may nevertheless predispose
	to or otherwise modify complex clinical phenotypes. Considerable
	efforts have been made to validate/elucidate the mechanisms through
	which the 3' untranslated region (3' UTR) variants affect gene expression.
	It is hoped that the integrative approach employed here in the study
	of naturally occurring variants of actual or potential pathological
	significance will serve to complement ongoing efforts to identify
	all functional regulatory elements in the human genome.},
	Author = {Chen, Jian-Min and F{\'{e}}rec, Claude and Cooper, David N.},
	Doi = {10.1007/s00439-006-0180-7},
	Institution = {INSERM, U613, 29220, Brest, France. Jian-Min.Chen@univ-brest.fr},
	Journal = {Hum Genet},
	Keywords = {3' Untranslated Regions, genetics; Base Sequence; Genetic Predisposition to Disease, genetics; Molecular Sequence Data; Mutation; Open Reading Frames, genetics; Polymorphism, Genetic; Regulatory Sequences, Nucleic Acid; Sequence Homology, Nucleic Acid},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Aug},
	Number = {1},
	Owner = {peter},
	Pages = {1--21},
	Pmid = {16645853},
	Timestamp = {2015.07.09},
	Title = {A systematic analysis of disease-associated variants in the 3' regulatory regions of human protein-coding genes {I}: general principles and overview.},
	Url = {http://dx.doi.org/10.1007/s00439-006-0180-7},
	Volume = {120},
	Year = {2006},
	Bdsk-Url-1 = {http://dx.doi.org/10.1007/s00439-006-0180-7}}

@article{Chuzhanova2007,
	Abstract = {The 3' untranslated regions (3' UTRs) of human protein-coding genes
	play a pivotal role in the regulation of mRNA 3' end formation, stability/degradation,
	nuclear export, subcellular localisation and translation, and hence
	are particularly rich in cis-acting regulatory elements. One recent
	addition to the already large repertoire of known cis-acting regulatory
	elements are the microRNA (miRNA) target sites that are present in
	the 3' UTRs of many human genes. miRNAs post-transcriptionally down-regulate
	gene expression by binding to complementary sequences on their cognate
	target mRNAs, thereby inducing either mRNA degradation or translational
	repression. To date, only one disease-associated 3' UTR variant (in
	the SLITRK1 gene) has been reported to occur within a bona fide miRNA
	binding site. By means of sequence complementarity, we have performed
	the first systematic search for potential miRNA-target site mutations
	within a set of 79 known disease-associated 3' UTR variants. Since
	no variants were found that either disrupted or created binding sites
	for known human miRNAs, we surmise that miRNA-target site mutations
	are not likely to represent a frequent cause of human genetic disease.},
	Author = {Chuzhanova, Nadia and Cooper, David N. and F{\'{e}}rec, Claude and Chen, Jian-Min},
	Doi = {10.1007/s11568-006-9000-3},
	Institution = {Institute of Medical Genetics, Cardiff University, Heath Park, Cardiff, CF14 4XN, UK.},
	Journal = {Genomic Med},
	Language = {eng},
	Medline-Pst = {ppublish},
	Number = {1-2},
	Owner = {peter},
	Pages = {29--33},
	Pmid = {18923926},
	Timestamp = {2015.07.25},
	Title = {Searching for potential {microRNA}-binding site mutations amongst known disease-associated 3' {UTR} variants.},
	Url = {http://dx.doi.org/10.1007/s11568-006-9000-3},
	Volume = {1},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1007/s11568-006-9000-3}}

@article{Cooper2005,
	Abstract = {Comparisons of orthologous genomic DNA sequences can be used to characterize
	regions that have been subject to purifying selection and are enriched
	for functional elements. We here present the results of such an analysis
	on an alignment of sequences from 29 mammalian species. The alignment
	captures approximately 3.9 neutral substitutions per site and spans
	approximately 1.9 Mbp of the human genome. We identify constrained
	elements from 3 bp to over 1 kbp in length, covering approximately
	5.5\% of the human locus. Our estimate for the total amount of nonexonic
	constraint experienced by this locus is roughly twice that for exonic
	constraint. Constrained elements tend to cluster, and we identify
	large constrained regions that correspond well with known functional
	elements. While constraint density inversely correlates with mobile
	element density, we also show the presence of unambiguously constrained
	elements overlapping mammalian ancestral repeats. In addition, we
	describe a number of elements in this region that have undergone
	intense purifying selection throughout mammalian evolution, and we
	show that these important elements are more numerous than previously
	thought. These results were obtained with Genomic Evolutionary Rate
	Profiling (GERP), a statistically rigorous and biologically transparent
	framework for constrained element identification. GERP identifies
	regions at high resolution that exhibit nucleotide substitution deficits,
	and measures these deficits as "rejected substitutions". Rejected
	substitutions reflect the intensity of past purifying selection and
	are used to rank and characterize constrained elements. We anticipate
	that GERP and the types of analyses it facilitates will provide further
	insights and improved annotation for the human genome as mammalian
	genome sequence data become richer.},
	Author = {Cooper, Gregory M. and Stone, Eric A. and Asimenos, George and , N. I. S. C Comparative Sequencing Program and Green, Eric D. and Batzoglou, Serafim and Sidow, Arend},
	Doi = {10.1101/gr.3577405},
	Institution = {Department of Genetics, Stanford University, Stanford, California 94305, USA.},
	Journal = {Genome Res},
	Keywords = {Animals; Base Sequence; Computational Biology, methods; Conserved Sequence; Cystic Fibrosis Transmembrane Conductance Regulator; Evolution, Molecular; Gene Components; Gene Expression Profiling, methods; Genome; Humans; Interspersed Repetitive Sequences; Mammals, genetics; Molecular Sequence Data; Sensitivity and Specificity; Sequence Alignment; Sequence Analysis, DNA; Sequence Homology, Nucleic Acid},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jul},
	Number = {7},
	Owner = {peter},
	Pages = {901--913},
	Pii = {gr.3577405},
	Pmid = {15965027},
	Timestamp = {2015.09.28},
	Title = {Distribution and intensity of constraint in mammalian genomic sequence.},
	Url = {http://dx.doi.org/10.1101/gr.3577405},
	Volume = {15},
	Year = {2005},
	Bdsk-Url-1 = {http://dx.doi.org/10.1101/gr.3577405}}

@article{Cooper2009,
	Abstract = {Cellular functions depend on numerous protein-coding and noncoding
	RNAs and the RNA-binding proteins associated with them, which form
	ribonucleoprotein complexes (RNPs). Mutations that disrupt either
	the RNA or protein components of RNPs or the factors required for
	their assembly can be deleterious. Alternative splicing provides
	cells with an exquisite capacity to fine-tune their transcriptome
	and proteome in response to cues. Splicing depends on a complex code,
	numerous RNA-binding proteins, and an enormously intricate network
	of interactions among them, increasing the opportunity for exposure
	to mutations and misregulation that cause disease. The discovery
	of disease-causing mutations in RNAs is yielding a wealth of new
	therapeutic targets, and the growing understanding of RNA biology
	and chemistry is providing new RNA-based tools for developing therapeutics.},
	Author = {Cooper, Thomas A. and Wan, Lili and Dreyfuss, Gideon},
	Doi = {10.1016/j.cell.2009.02.011},
	Institution = {Department of Pathology, Baylor College of Medicine, Houston, TX 77030, USA. tcooper@bcm.tmc.edu},
	Journal = {Cell},
	Keywords = {Alternative Splicing; Disease, genetics; Mutation; RNA Splicing; RNA, therapeutic use; Therapeutics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Feb},
	Number = {4},
	Owner = {peter},
	Pages = {777--793},
	Pii = {S0092-8674(09)00148-2},
	Pmid = {19239895},
	Timestamp = {2015.08.27},
	Title = {RNA and disease.},
	Url = {http://dx.doi.org/10.1016/j.cell.2009.02.011},
	Volume = {136},
	Year = {2009},
	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.cell.2009.02.011}}

@article{Cor95,
	Author = {Cortes, C. and Vapnik, V.},
	Journal = {Machine Learning},
	Pages = {273--297},
	Title = {Support vector networks},
	Volume = {20},
	Year = {1995}}

@article{DeLong1988,
	Abstract = {Methods of evaluating and comparing the performance of diagnostic
	tests are of increasing importance as new tests are developed and
	marketed. When a test is based on an observed variable that lies
	on a continuous or graded scale, an assessment of the overall value
	of the test can be made through the use of a receiver operating characteristic
	(ROC) curve. The curve is constructed by varying the cutpoint used
	to determine which values of the observed variable will be considered
	abnormal and then plotting the resulting sensitivities against the
	corresponding false positive rates. When two or more empirical curves
	are constructed based on tests performed on the same individuals,
	statistical analysis on differences between curves must take into
	account the correlated nature of the data. This paper presents a
	nonparametric approach to the analysis of areas under correlated
	ROC curves, by using the theory on generalized U-statistics to generate
	an estimated covariance matrix.},
	Author = {DeLong, E R and DeLong, D M and Clarke-Pearson, D L},
	Issn = {0006-341X},
	Journal = {Biometrics},
	Keywords = {Algorithms,Analysis of Variance,Female,Humans,Intestinal Obstruction,Intestinal Obstruction: surgery,Models, Statistical,Ovarian Neoplasms,Ovarian Neoplasms: complications,Predictive Value of Tests,ROC Curve},
	Month = sep,
	Number = {3},
	Pages = {837--45},
	Pmid = {3203132},
	Title = {{Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.}},
	Url = {http://www.ncbi.nlm.nih.gov/pubmed/3203132},
	Volume = {44},
	Year = {1988},
	Bdsk-Url-1 = {http://www.ncbi.nlm.nih.gov/pubmed/3203132}}

@article{Dixon2012,
	Abstract = {The spatial organization of the genome is intimately linked to its
	biological function, yet our understanding of higher order genomic
	structure is coarse, fragmented and incomplete. In the nucleus of
	eukaryotic cells, interphase chromosomes occupy distinct chromosome
	territories, and numerous models have been proposed for how chromosomes
	fold within chromosome territories. These models, however, provide
	only few mechanistic details about the relationship between higher
	order chromatin structure and genome function. Recent advances in
	genomic technologies have led to rapid advances in the study of three-dimensional
	genome organization. In particular, Hi-C has been introduced as a
	method for identifying higher order chromatin interactions genome
	wide. Here we investigate the three-dimensional organization of the
	human and mouse genomes in embryonic stem cells and terminally differentiated
	cell types at unprecedented resolution. We identify large, megabase-sized
	local chromatin interaction domains, which we term 'topological domains',
	as a pervasive structural feature of the genome organization. These
	domains correlate with regions of the genome that constrain the spread
	of heterochromatin. The domains are stable across different cell
	types and highly conserved across species, indicating that topological
	domains are an inherent property of mammalian genomes. Finally, we
	find that the boundaries of topological domains are enriched for
	the insulator binding protein CTCF, housekeeping genes, transfer
	RNAs and short interspersed element (SINE) retrotransposons, indicating
	that these factors may have a role in establishing the topological
	domain structure of the genome.},
	Author = {Dixon, Jesse R. and Selvaraj, Siddarth and Yue, Feng and Kim, Audrey and Li, Yan and Shen, Yin and Hu, Ming and Liu, Jun S. and Ren, Bing},
	Doi = {10.1038/nature11082},
	Institution = {Ludwig Institute for Cancer Research, 9500 Gilman Drive, La Jolla, California 92093, USA.},
	Journal = {Nature},
	Keywords = {Animals; Binding Sites; Cell Differentiation; Chromatin, chemistry/genetics/metabolism; Chromosomes, chemistry/genetics/metabolism; Embryonic Stem Cells, metabolism; Evolution, Molecular; Female; Genes, Essential, genetics; Genome; Heterochromatin, chemistry/genetics/metabolism; Humans; Male; Mammals, genetics; Mice; RNA, Transfer, genetics; Repressor Proteins, metabolism; Short Interspersed Nucleotide Elements, genetics},
	Language = {eng},
	Medline-Pst = {epublish},
	Month = {May},
	Number = {7398},
	Owner = {peter},
	Pages = {376--380},
	Pii = {nature11082},
	Pmid = {22495300},
	Timestamp = {2015.06.13},
	Title = {Topological domains in mammalian genomes identified by analysis of chromatin interactions.},
	Url = {http://dx.doi.org/10.1038/nature11082},
	Volume = {485},
	Year = {2012},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nature11082}}

@inproceedings{Domingos99,
	Address = {New York, NY, USA},
	Author = {Domingos, P.},
	Booktitle = {Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
	Location = {San Diego, California, USA},
	Pages = {155--164},
	Publisher = {ACM},
	Series = {KDD '99},
	Title = {MetaCost: A General Method for Making Classifiers Cost-sensitive},
	Year = {1999}}

@article{Dorschner2013,
	Abstract = {The incorporation of genomics into medicine is stimulating interest
	on the return of incidental findings (IFs) from exome and genome
	sequencing. However, no large-scale study has yet estimated the number
	of expected actionable findings per individual; therefore, we classified
	actionable pathogenic single-nucleotide variants in 500 European-
	and 500 African-descent participants randomly selected from the National
	Heart, Lung, and Blood Institute Exome Sequencing Project. The 1,000
	individuals were screened for variants in 114 genes selected by an
	expert panel for their association with medically actionable genetic
	conditions possibly undiagnosed in adults. Among the 1,000 participants,
	585 instances of 239 unique variants were identified as disease causing
	in the Human Gene Mutation Database (HGMD). The primary literature
	supporting the variants' pathogenicity was reviewed. Of the identified
	IFs, only 16 unique autosomal-dominant variants in 17 individuals
	were assessed to be pathogenic or likely pathogenic, and one participant
	had two pathogenic variants for an autosomal-recessive disease. Furthermore,
	one pathogenic and four likely pathogenic variants not listed as
	disease causing in HGMD were identified. These data can provide an
	estimate of the frequency (3.4\% for European descent and 1.2\% for
	African descent) of the high-penetrance actionable pathogenic or
	likely pathogenic variants in adults. The 23 participants with pathogenic
	or likely pathogenic variants were disproportionately of European
	(17) versus African (6) descent. The process of classifying these
	variants underscores the need for a more comprehensive and diverse
	centralized resource to provide curated information on pathogenicity
	for clinical use to minimize health disparities in genomic medicine.},
	Author = {Dorschner, Michael O. and Amendola, Laura M. and Turner, Emily H. and Robertson, Peggy D. and Shirts, Brian H. and Gallego, Carlos J. and Bennett, Robin L. and Jones, Kelly L. and Tokita, Mari J. and Bennett, James T. and Kim, Jerry H. and Rosenthal, Elisabeth A. and Kim, Daniel S. and {National Heart, Lung and Blood Institute Grand Opportunity Exome Sequencing Project} and Tabor, Holly K. and Bamshad, Michael J. and Motulsky, Arno G. and Scott, C Ronald and Pritchard, Colin C. and Walsh, Tom and Burke, Wylie and Raskind, Wendy H. and Byers, Peter and Hisama, Fuki M. and Nickerson, Deborah A. and Jarvik, Gail P.},
	Doi = {10.1016/j.ajhg.2013.08.006},
	Institution = {Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA; Department of Laboratory Medicine, University of Washington, Seattle, WA 98195, USA.},
	Journal = {Am J Hum Genet},
	Keywords = {Databases, Genetic; Disease, genetics; Exome; Gene Frequency; Genetic Predisposition to Disease; Humans; Incidental Findings; Penetrance; Polymorphism, Single Nucleotide},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Oct},
	Number = {4},
	Owner = {peter},
	Pages = {631--640},
	Pii = {S0002-9297(13)00381-9},
	Pmid = {24055113},
	Timestamp = {2015.08.09},
	Title = {Actionable, pathogenic incidental findings in 1,000 participants' exomes.},
	Url = {http://dx.doi.org/10.1016/j.ajhg.2013.08.006},
	Volume = {93},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.ajhg.2013.08.006}}

@article{Edwards2013,
	Abstract = {Genome-wide association studies (GWASs) have enabled the discovery
	of common genetic variation contributing to normal and pathological
	traits and clinical drug responses, but recognizing the precise targets
	of these associations is now the major challenge. Here, we review
	recent approaches to the functional follow-up of GWAS loci, including
	fine mapping of GWAS signal(s), prioritization of putative functional
	SNPs by the integration of genetic epidemiological and bioinformatic
	methods, and in vitro and in vivo experimental verification of predicted
	molecular mechanisms for identifying the targeted genes. The majority
	of GWAS-identified variants fall in noncoding regions of the genome.
	Therefore, this review focuses on strategies for assessing likely
	mechanisms affected by noncoding variants; such mechanisms include
	transcriptional regulation, noncoding RNA function, and epigenetic
	regulation. These approaches have already accelerated progress from
	genetic studies to biological knowledge and might ultimately guide
	the development of prognostic, preventive, and therapeutic measures.},
	Author = {Edwards, Stacey L. and Beesley, Jonathan and French, Juliet D. and Dunning, Alison M.},
	Doi = {10.1016/j.ajhg.2013.10.012},
	Institution = {Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland 4029, Australia; School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Queensland 4072, Australia. Electronic address: stacey.edwards@qimrberghofer.edu.au.},
	Journal = {Am J Hum Genet},
	Keywords = {Animals; Chromosome Mapping; Computational Biology; Epigenesis, Genetic; Genetic Loci; Genetic Predisposition to Disease, genetics; Genome-Wide Association Study; Humans; Neoplasms, genetics/pathology; Phenotype; Polymorphism, Single Nucleotide; RNA, Untranslated, genetics; Risk Factors},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Nov},
	Number = {5},
	Owner = {peter},
	Pages = {779--797},
	Pii = {S0002-9297(13)00469-2},
	Pmid = {24210251},
	Timestamp = {2015.08.08},
	Title = {Beyond {GWASs}: illuminating the dark road from association to function.},
	Url = {http://dx.doi.org/10.1016/j.ajhg.2013.10.012},
	Volume = {93},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.ajhg.2013.10.012}}

@Article{Eilbeck2005,
  author      = {Eilbeck, Karen and Lewis, Suzanna E. and Mungall, Christopher J. and Yandell, Mark and Stein, Lincoln and Durbin, Richard and Ashburner, Michael},
  title       = {The Sequence Ontology: a tool for the unification of genome annotations.},
  journal     = {Genome Biol},
  year        = {2005},
  volume      = {6},
  number      = {5},
  pages       = {R44},
  abstract    = {The Sequence Ontology (SO) is a structured controlled vocabulary for
	the parts of a genomic annotation. SO provides a common set of terms
	and definitions that will facilitate the exchange, analysis and management
	of genomic data. Because SO treats part-whole relationships rigorously,
	data described with it can become substrates for automated reasoning,
	and instances of sequence features described by the SO can be subjected
	to a group of logical operations termed extensional mereology operators.},
  bdsk-url-1  = {http://dx.doi.org/10.1186/gb-2005-6-5-r44},
  doi         = {10.1186/gb-2005-6-5-r44},
  institution = {Department of Molecular and Cellular Biology, Life Sciences Addition, University of California, Berkeley, CA 94729-3200, USA. keilbeck@fruitfly.org},
  keywords    = {Alternative Splicing; Computational Biology; Databases, Genetic; Documentation; Exons; Genomics, methods; RNA, Messenger, classification; Software Design; Terminology as Topic; Vocabulary, Controlled},
  language    = {eng},
  medline-pst = {ppublish},
  owner       = {peter},
  pii         = {gb-2005-6-5-r44},
  pmid        = {15892872},
  timestamp   = {2015.10.17},
  url         = {http://dx.doi.org/10.1186/gb-2005-6-5-r44},
}

@inproceedings{Elkan01,
	Address = {San Francisco, CA, USA},
	Author = {Elkan, C.},
	Booktitle = {Proceedings of the 17th International Joint Conference on Artificial Intelligence - Volume 2},
	Location = {Seattle, WA, USA},
	Pages = {973--978},
	Publisher = {Morgan Kaufmann Publishers Inc.},
	Series = {IJCAI'01},
	Title = {The Foundations of Cost-sensitive Learning},
	Year = {2001}}

@article{Epstein2009,
	Abstract = {Cis-acting regulatory sequences are required for the proper temporal
	and spatial control of gene expression. Variation in gene expression
	is highly heritable and a significant determinant of human disease
	susceptibility. The diversity of human genetic diseases attributed,
	in whole or in part, to mutations in non-coding regulatory sequences
	is on the rise. Improvements in genome-wide methods of associating
	genetic variation with human disease and predicting DNA with cis-regulatory
	potential are two of the major reasons for these recent advances.
	This review will highlight select examples from the literature that
	have successfully integrated genetic and genomic approaches to uncover
	the molecular basis by which cis-regulatory mutations alter gene
	expression and contribute to human disease. The fine mapping of disease-causing
	variants has led to the discovery of novel cis-acting regulatory
	elements that, in some instances, are located as far away as 1.5
	Mb from the target gene. In other cases, the prior knowledge of the
	regulatory landscape surrounding the gene of interest aided in the
	selection of enhancers for mutation screening. The success of these
	studies should provide a framework for following up on the large
	number of genome-wide association studies that have identified common
	variants in non-coding regions of the genome that associate with
	increased risk of human diseases including, diabetes, autism, Crohn's,
	colorectal cancer, and asthma, to name a few.},
	Author = {Epstein, Douglas J.},
	Doi = {10.1093/bfgp/elp021},
	Institution = {Department of Genetics, University of Pennsylvania School of Medicine, Clinical Research Bldg, Room 470, 415 Curie Blvd, Philadelphia, PA 19104, USA. epsteind@mail.med.upenn.edu},
	Journal = {Brief Funct Genomic Proteomic},
	Keywords = {Disease, genetics; Gene Expression Regulation; Humans; Mutation, genetics; Regulatory Sequences, Nucleic Acid, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jul},
	Number = {4},
	Owner = {peter},
	Pages = {310--316},
	Pii = {elp021},
	Pmid = {19641089},
	Timestamp = {2015.07.18},
	Title = {Cis-regulatory mutations in human disease.},
	Url = {http://dx.doi.org/10.1093/bfgp/elp021},
	Volume = {8},
	Year = {2009},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/bfgp/elp021}}

@article{Galar12,
	Author = {Galar, M. and Fernandez, A. and Barrenechea, E. and Bustince, H. and Herrera, F.},
	Journal = {Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on},
	Month = {July},
	Number = {4},
	Pages = {463-484},
	Title = {A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches},
	Volume = {42},
	Year = {2012}}

@article{Giardine2007,
	Abstract = {HbVar (http://globin.bx.psu.edu/hbvar) is a locus-specific database
	(LSDB) developed in 2001 by a multi-center academic effort to provide
	timely information on the genomic sequence changes leading to hemoglobin
	variants and all types of thalassemia and hemoglobinopathies. Database
	records include extensive phenotypic descriptions, biochemical and
	hematological effects, associated pathology, and ethnic occurrence,
	accompanied by mutation frequencies and references. In addition to
	the regular updates to entries, we report significant advances and
	updates, which can be useful not only for HbVar users but also for
	other LSDB development and curation in general. The query page provides
	more functionality but in a simpler, more user-friendly format and
	known single nucleotide polymorphisms in the human alpha- and beta-globin
	loci are provided automatically. Population-specific beta-thalassemia
	mutation frequencies for 31 population groups have been added and/or
	modified and the previously reported delta- and alpha-thalassemia
	mutation frequency data from 10 population groups have also been
	incorporated. In addition, an independent flat-file database, named
	XPRbase (http://www.goldenhelix.org/xprbase), has been developed
	and linked to the main HbVar web page to provide a succinct listing
	of 51 experimental protocols available for globin gene mutation screening.
	These updates significantly augment the database profile and quality
	of information provided, which should increase the already high impact
	of the HbVar database, while its combination with the UCSC powerful
	genome browser and the ITHANET web portal paves the way for drawing
	connections of clinical importance, that is from genome to function
	to phenotype.},
	Author = {Giardine, Belinda and {van Baal}, Sjozef and Kaimakis, Polynikis and Riemer, Cathy and Miller, Webb and Samara, Maria and Kollia, Panagoula and Anagnou, Nicholas P. and Chui, David H K. and Wajcman, Henri and Hardison, Ross C. and Patrinos, George P.},
	Doi = {10.1002/humu.9479},
	Institution = {The Pennsylvania State University, Center for Comparative Genomics and Bioinformatics, University Park, Pennsylvania, USA.},
	Journal = {Hum Mutat},
	Keywords = {DNA Mutational Analysis, methods; Databases, Nucleic Acid; Genetic Testing, methods; Genetic Variation; Hemoglobins, genetics; Humans; Multigene Family; Mutation; Thalassemia, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Feb},
	Number = {2},
	Owner = {peter},
	Pages = {206},
	Pmid = {17221864},
	Timestamp = {2015.08.28},
	Title = {HbVar database of human hemoglobin variants and thalassemia mutations: 2007 update.},
	Url = {http://dx.doi.org/10.1002/humu.9479},
	Volume = {28},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/humu.9479}}

@article{Gilissen2014,
	Abstract = {Severe intellectual disability (ID) occurs in 0.5\% of newborns and
	is thought to be largely genetic in origin. The extensive genetic
	heterogeneity of this disorder requires a genome-wide detection of
	all types of genetic variation. Microarray studies and, more recently,
	exome sequencing have demonstrated the importance of de novo copy
	number variations (CNVs) and single-nucleotide variations (SNVs)
	in ID, but the majority of cases remain undiagnosed. Here we applied
	whole-genome sequencing to 50 patients with severe ID and their unaffected
	parents. All patients included had not received a molecular diagnosis
	after extensive genetic prescreening, including microarray-based
	CNV studies and exome sequencing. Notwithstanding this prescreening,
	84 de novo SNVs affecting the coding region were identified, which
	showed a statistically significant enrichment of loss-of-function
	mutations as well as an enrichment for genes previously implicated
	in ID-related disorders. In addition, we identified eight de novo
	CNVs, including single-exon and intra-exonic deletions, as well as
	interchromosomal duplications. These CNVs affected known ID genes
	more frequently than expected. On the basis of diagnostic interpretation
	of all de novo variants, a conclusive genetic diagnosis was reached
	in 20 patients. Together with one compound heterozygous CNV causing
	disease in a recessive mode, this results in a diagnostic yield of
	42\% in this extensively studied cohort, and 62\% as a cumulative
	estimate in an unselected cohort. These results suggest that de novo
	SNVs and CNVs affecting the coding region are a major cause of severe
	ID. Genome sequencing can be applied as a single genetic test to
	reliably identify and characterize the comprehensive spectrum of
	genetic variation, providing a genetic diagnosis in the majority
	of patients with severe ID.},
	Author = {Gilissen, Christian and Hehir-Kwa, Jayne Y. and Thung, Djie Tjwan and {van de Vorst}, Maartje and {van Bon}, Bregje W M. and Willemsen, Marjolein H. and Kwint, Michael and Janssen, Irene M. and Hoischen, Alexander and Schenck, Annette and Leach, Richard and Klein, Robert and Tearle, Rick and Bo, Tan and Pfundt, Rolph and Yntema, Helger G. and {de Vries}, Bert B A. and Kleefstra, Tjitske and Brunner, Han G. and Vissers, Lisenka E L M. and Veltman, Joris A.},
	Doi = {10.1038/nature13394},
	Institution = {Department of Clinical Genetics, Maastricht University Medical Centre. Universiteitssingel 50, 6229 ER Maastricht, the Netherlands [3].},
	Journal = {Nature},
	Keywords = {Chromosomes, Human, Pair 4, genetics; Chromosomes, Human, X, genetics; Cohort Studies; DNA Copy Number Variations, genetics; Gene Duplication, genetics; Genome, Human, genetics; Guanine Nucleotide Exchange Factors, genetics; Humans; Intellectual Disability, genetics; Male; Mutation, genetics; Polymorphism, Single Nucleotide, genetics; Sequence Analysis, DNA},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jul},
	Number = {7509},
	Owner = {peter},
	Pages = {344--347},
	Pii = {nature13394},
	Pmid = {24896178},
	Timestamp = {2015.08.05},
	Title = {Genome sequencing identifies major causes of severe intellectual disability.},
	Url = {http://dx.doi.org/10.1038/nature13394},
	Volume = {511},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nature13394}}

@article{Gordon2014,
	Abstract = {Only a few mutations in regulatory elements that cause human disease
	have been identified thus far. A new report identifies cis-regulatory
	mutations that abolish the activity of a developmental enhancer,
	thereby causing pancreatic agenesis.},
	Author = {Gordon, Christopher T. and Lyonnet, Stanislas},
	Doi = {10.1038/ng.2861},
	Institution = {University Paris Descartes-Sorbonne, Paris Cit{\'e}, Institut Imagine, INSERM U781, H{\^o}pital Necker-Enfants Malades, Paris, France.},
	Journal = {Nat Genet},
	Keywords = {Enhancer Elements, Genetic, genetics; Female; Humans; Male; Mutation; Pancreas, abnormalities; Pancreatic Diseases, congenital/genetics; Transcription Factors, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {1},
	Owner = {peter},
	Pages = {3--4},
	Pii = {ng.2861},
	Pmid = {24370740},
	Timestamp = {2015.07.09},
	Title = {Enhancer mutations and phenotype modularity.},
	Url = {http://dx.doi.org/10.1038/ng.2861},
	Volume = {46},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/ng.2861}}

@article{Gout2007,
	Author = {Gout, Alexander M. and , A. D. P. K. D Gene Variant Consortium and Ravine, David and Harris, Peter C. and Rossetti, Sandro and Peters, Dorien and Breuning, Martijn and Henske, Elizabeth Petri and Koizumi, Akio and Inoue, Sumiko and Shimizu, Yoshiko and Thongnoppakhun, Wanna and Yenchitsomanus, Pa-thai and Deltas, Constantinos and Sandford, Richard and Torra, Roser and Turco, Alberto E. and Jeffery, Steve and Fontes, Michel and Somlo, Stefan and Furu, Laszlo M. and Smulders, Yvo M. and Mercier, Bernard and Ferec, Claude and Burtey, St{\'{e}}phane and Pei, York and Kalaydjieva, Luba and Bogdanova, Nadja and McCluskey, Marie and Geon, Lee Jung and Wouters, C. H. and Reiterova, Jana and Stekrov{\'{a}}, Jitka and {San Millan}, Jose L. and Aguiari, Gianluca and {Del Senno}, Laura},
	Doi = {10.1038/ng0407-427},
	Journal = {Nat Genet},
	Keywords = {Base Sequence; Humans; Peer Review, Research, standards; Polymorphism, Genetic; Research Design; TRPP Cation Channels},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Apr},
	Number = {4},
	Owner = {peter},
	Pages = {427--428},
	Pii = {ng0407-427},
	Pmid = {17392796},
	Timestamp = {2015.08.09},
	Title = {Analysis of published {PKD1} gene sequence variants.},
	Url = {http://dx.doi.org/10.1038/ng0407-427},
	Volume = {39},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/ng0407-427}}

@article{Gulko2015,
	Abstract = {We describe a new computational method for estimating the probability
	that a point mutation at each position in a genome will influence
	fitness. These 'fitness consequence' (fitCons) scores serve as evolution-based
	measures of potential genomic function. Our approach is to cluster
	genomic positions into groups exhibiting distinct 'fingerprints'
	on the basis of high-throughput functional genomic data, then to
	estimate a probability of fitness consequences for each group from
	associated patterns of genetic polymorphism and divergence. We have
	generated fitCons scores for three human cell types on the basis
	of public data from ENCODE. In comparison with conventional conservation
	scores, fitCons scores show considerably improved prediction power
	for cis regulatory elements. In addition, fitCons scores indicate
	that 4.2-7.5\% of nucleotides in the human genome have influenced
	fitness since the human-chimpanzee divergence, and they suggest that
	recent evolutionary turnover has had limited impact on the functional
	content of the genome.},
	Author = {Gulko, Brad and Hubisz, Melissa J. and Gronau, Ilan and Siepel, Adam},
	Doi = {10.1038/ng.3196},
	Institution = {Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, New York, USA.},
	Journal = {Nat Genet},
	Keywords = {Animals; Cell Line; Evolution, Molecular; Genetic Fitness; Genome, Human; Human Umbilical Vein Endothelial Cells; Humans; Pan troglodytes, genetics; Point Mutation; Polymorphism, Genetic; Probability; Regulatory Sequences, Nucleic Acid},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Mar},
	Number = {3},
	Owner = {peter},
	Pages = {276--283},
	Pii = {ng.3196},
	Pmid = {25599402},
	Timestamp = {2015.09.27},
	Title = {A method for calculating probabilities of fitness consequences for point mutations across the human genome.},
	Url = {http://dx.doi.org/10.1038/ng.3196},
	Volume = {47},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/ng.3196}}

@article{Hall2009,
	Author = {Hall, Mark and Frank, Eibe and Holmes, Geoffrey and Pfahringer, Bernhard and Reutemann, Peter and Witten, Ian H.},
	Doi = {10.1145/1656274.1656278},
	Issn = {19310145},
	Journal = {ACM SIGKDD Explorations Newsletter},
	Mendeley-Groups = {Bioinformatic/Genomiser},
	Month = nov,
	Number = {1},
	Pages = {10},
	Publisher = {ACM},
	Title = {{The WEKA data mining software}},
	Url = {http://dl.acm.org/citation.cfm?id=1656274.1656278},
	Volume = {11},
	Year = {2009},
	Bdsk-Url-1 = {http://dl.acm.org/citation.cfm?id=1656274.1656278},
	Bdsk-Url-2 = {http://dx.doi.org/10.1145/1656274.1656278}}

@article{he09,
	Author = {He, Haibo and Garcia, Edwardo and others},
	Date-Added = {2015-09-22 17:29:53 +0000},
	Date-Modified = {2015-09-22 17:30:07 +0000},
	Journal = {Knowledge and Data Engineering, IEEE Transactions on},
	Number = {9},
	Pages = {1263--1284},
	Publisher = {IEEE},
	Title = {Learning from imbalanced data},
	Volume = {21},
	Year = {2009}}

@article{Hrdlickova2014,
	Abstract = {It has been found that the majority of disease-associated genetic
	variants identified by genome-wide association studies are located
	outside of protein-coding regions, where they seem to affect regions
	that control transcription (promoters, enhancers) and non-coding
	RNAs that also can influence gene expression. In this review, we
	focus on two classes of non-coding RNAs that are currently a major
	focus of interest: micro-RNAs and long non-coding RNAs. We describe
	their biogenesis, suggested mechanism of action, and discuss how
	these non-coding RNAs might be affected by disease-associated genetic
	alterations. The discovery of these alterations has already contributed
	to a better understanding of the etiopathology of human diseases
	and yielded insight into the function of these non-coding RNAs. We
	also provide an overview of available databases, bioinformatics tools,
	and high-throughput techniques that can be used to study the mechanism
	of action of individual non-coding RNAs. This article is part of
	a Special Issue entitled: From Genome to Function.},
	Author = {Hrdlickova, Barbara and {de Almeida}, Rodrigo Coutinho and Borek, Zuzanna and Withoff, Sebo},
	Doi = {10.1016/j.bbadis.2014.03.011},
	Institution = {Department of Genetics, University of Groningen, University Medical Center Groningen, The Netherlands.},
	Journal = {Biochim Biophys Acta},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Oct},
	Number = {10},
	Owner = {peter},
	Pages = {1910--1922},
	Pii = {S0925-4439(14)00071-4},
	Pmid = {24667321},
	Timestamp = {2015.08.27},
	Title = {Genetic variation in the non-coding genome: Involvement of micro-RNAs and long non-coding RNAs in disease.},
	Url = {http://dx.doi.org/10.1016/j.bbadis.2014.03.011},
	Volume = {1842},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.bbadis.2014.03.011}}

@article{Ibn-Salem2014,
	Abstract = {Recent data from genome-wide chromosome conformation capture analysis
	indicate that the human genome is divided into conserved megabase-sized
	self-interacting regions called topological domains. These topological
	domains form the regulatory backbone of the genome and are separated
	by regulatory boundary elements or barriers. Copy-number variations
	can potentially alter the topological domain architecture by deleting
	or duplicating the barriers and thereby allowing enhancers from neighboring
	domains to ectopically activate genes causing misexpression and disease,
	a mutational mechanism that has recently been termed enhancer adoption.We
	use the Human Phenotype Ontology database to relate the phenotypes
	of 922 deletion cases recorded in the DECIPHER database to monogenic
	diseases associated with genes in or adjacent to the deletions. We
	identify combinations of tissue-specific enhancers and genes adjacent
	to the deletion and associated with phenotypes in the corresponding
	tissue, whereby the phenotype matched that observed in the deletion.
	We compare this computationally with a gene-dosage pathomechanism
	that attempts to explain the deletion phenotype based on haploinsufficiency
	of genes located within the deletions. Up to 11.8\% of the deletions
	could be best explained by enhancer adoption or a combination of
	enhancer adoption and gene-dosage effects.Our results suggest that
	enhancer adoption caused by deletions of regulatory boundaries may
	contribute to a substantial minority of copy-number variation phenotypes
	and should thus be taken into account in their medical interpretation.},
	Author = {Ibn-Salem, Jonas and K{\"o}hler, Sebastian and Love, Michael I. and Chung, Ho-Ryun and Huang, Ni and Hurles, Matthew E. and Haendel, Melissa and Washington, Nicole L. and Smedley, Damian and Mungall, Christopher J. and Lewis, Suzanna E. and Ott, Claus-Eric and Bauer, Sebastian and Schofield, Paul N. and Mundlos, Stefan and Spielmann, Malte and Robinson, Peter N.},
	Doi = {10.1186/s13059-014-0423-1},
	Journal = {Genome Biol},
	Language = {eng},
	Medline-Pst = {epublish},
	Number = {9},
	Owner = {peter},
	Pages = {423},
	Pii = {s13059-014-0423-1},
	Pmid = {25315429},
	Timestamp = {2015.08.09},
	Title = {Deletions of chromosomal regulatory boundaries are associated with congenital disease.},
	Url = {http://dx.doi.org/10.1186/s13059-014-0423-1},
	Volume = {15},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/s13059-014-0423-1}}

@article{Jager2014,
	Abstract = {Transcript-based annotation and pedigree analysis are two basic steps
	in the computational analysis of whole-exome sequencing experiments
	in genetic diagnostics and disease-gene discovery projects. Here,
	we present Jannovar, a stand-alone Java application as well as a
	Java library designed to be used in larger software frameworks for
	exome and genome analysis. Jannovar uses an interval tree to identify
	all transcripts affected by a given variant, and provides Human Genome
	Variation Society-compliant annotations both for variants affecting
	coding sequences and splice junctions as well as untranslated regions
	and noncoding RNA transcripts. Jannovar can also perform family-based
	pedigree analysis with Variant Call Format (VCF) files with data
	from members of a family segregating a Mendelian disorder. Using
	a desktop computer, Jannovar requires a few seconds to annotate a
	typical VCF file with exome data. Jannovar is freely available under
	the BSD2 license. Source code as well as the Java application and
	library file can be downloaded from http://compbio.charite.de (with
	tutorial) and https://github.com/charite/jannovar.},
	Author = {J\"{a}ger, Marten and Wang, Kai and Bauer, Sebastian and Smedley, Damian and Krawitz, Peter and Robinson, Peter N},
	Doi = {10.1002/humu.22531},
	Isbn = {10597794},
	Issn = {1098-1004},
	Journal = {Human mutation},
	Keywords = {bioinformatics,exome sequencing,genomic annotation,in-,terval tree},
	Mendeley-Groups = {GFH},
	Number = {5},
	Pages = {548--55},
	Pmid = {24677618},
	Title = {{Jannovar: a java library for exome annotation.}},
	Url = {http://www.ncbi.nlm.nih.gov/pubmed/24677618},
	Volume = {35},
	Year = {2014},
	Bdsk-Url-1 = {http://www.ncbi.nlm.nih.gov/pubmed/24677618},
	Bdsk-Url-2 = {http://dx.doi.org/10.1002/humu.22531}}

@article{Jarinova2012,
	Abstract = {With the successful identification of many protein-coding genes, the
	focus has now shifted toward deciphering functions of non-protein-coding
	regions that direct spatiotemporal and quantitative aspects of protein
	expression. Recent advances in our understanding of the regulatory
	architecture of the human genome coincide with growing evidence that
	changes in regulatory sequences are associated with human disease.
	Several recent reviews have highlighted disease-causing potential
	of aberrations in transcriptional and splicing regulatory elements
	as well as non-protein-coding RNA. Although changes in regulatory
	sequences generally produce milder biological effects than their
	protein-coding counterparts, many act as independent risk factors
	for common complex disorders or as genetic modifiers for "primary"
	disease-causing loci. Here, we review bioinformatics and experimental
	approaches that are used to identify regulatory sequences and assess
	pathogenicity of regulatory changes. We describe the current state
	of knowledge on disease-causing changes in regulatory sequences,
	challenge protein-centric views, and discuss complexities and solutions
	pertaining to the interpretation of regulatory changes in the next-generation
	sequencing era.},
	Author = {Jarinova, Olga and Ekker, Marc},
	Doi = {10.1002/humu.22083},
	Institution = {Molecular Diagnostics Laboratory, Department of Genetics, Children's Hospital of Eastern Ontario, 401 Smyth Rd., Ottawa, Ontario, Canada. ojarinova@cheo.on.ca},
	Journal = {Hum Mutat},
	Keywords = {Genome, Human, genetics; Humans; Pathology, Molecular, methods; Regulatory Sequences, Nucleic Acid, genetics; Sequence Analysis, DNA, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jul},
	Number = {7},
	Owner = {peter},
	Pages = {1021--1030},
	Pmid = {22431194},
	Timestamp = {2015.08.06},
	Title = {Regulatory variations in the era of next-generation sequencing: implications for clinical molecular diagnostics.},
	Url = {http://dx.doi.org/10.1002/humu.22083},
	Volume = {33},
	Year = {2012},
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/humu.22083}}

@article{Javed2014,
	Abstract = {We introduce Phen-Gen, a method that combines patients' disease symptoms
	and sequencing data with prior domain knowledge to identify the causative
	genes for rare disorders. Simulations revealed that the causal variant
	was ranked first in 88\% of cases when it was a coding variant-a
	52\% advantage over a genotype-only approach-and Phen-Gen outperformed
	other existing prediction methods by 13-58\%. If disease etiology
	was unknown, the causal variant was assigned the top rank in 71\%
	of simulations. Phen-Gen is available at http://phen-gen.org/.},
	Author = {Javed, Asif and Agrawal, Saloni and Ng, Pauline C.},
	Doi = {10.1038/nmeth.3046},
	Institution = {Computational and Systems Biology Group, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore.},
	Journal = {Nat Methods},
	Keywords = {Chromosome Mapping, methods; Data Mining, methods; Databases, Genetic; Genetic Predisposition to Disease, genetics; Genetic Testing, methods; Genome, Human, genetics; Genotype; Humans; Phenotype; Polymorphism, Single Nucleotide, genetics; Rare Diseases, diagnosis/genetics; Software},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Sep},
	Number = {9},
	Owner = {peter},
	Pages = {935--937},
	Pii = {nmeth.3046},
	Pmid = {25086502},
	Timestamp = {2015.08.09},
	Title = {{Phen-Gen}: combining phenotype and genotype to analyze rare disorders.},
	Url = {http://dx.doi.org/10.1038/nmeth.3046},
	Volume = {11},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nmeth.3046}}

@article{Jones2011,
	Abstract = {Cis-acting polymorphisms that affect gene expression are now known
	to be frequent, although the extent and mechanisms by which such
	variation affects the human phenotype are, as yet, only poorly understood.
	Key signatures of cis-acting variation are differences in gene expression
	that are tightly associated with regulatory SNPs or expression Quantitative
	Trait Loci (eQTL) and an imbalance of allelic expression (AEI) in
	heterozygous samples. Such cis-acting sequence differences appear
	often to have been under selection within and between populations
	and are also thought to be important in speciation. Here we describe
	the example of lactase persistence. In medical research, variants
	that affect regulation in cis have been implicated in both monogenic
	and polygenic disorders, and in the metabolism of drugs. In this
	review we suggest that by further understanding common regulatory
	variations and how they interact with other genetic and environmental
	variables it will be possible to gain insight into important mechanisms
	behind complex disease, with the potential to lead to new methods
	of diagnosis and treatments.},
	Author = {Jones, Bryony L. and Swallow, Dallas M.},
	Doi = {10.1007/s11568-011-9155-4},
	Institution = {Research Department of Genetics, Evolution and Environment, University College London, Darwin Building, Gower Street, London, WC1E 6BT UK.},
	Journal = {Hugo J},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Dec},
	Number = {1-4},
	Owner = {peter},
	Pages = {13--23},
	Pii = {9155},
	Pmid = {23205161},
	Timestamp = {2015.08.04},
	Title = {The impact of cis-acting polymorphisms on the human phenotype.},
	Url = {http://dx.doi.org/10.1007/s11568-011-9155-4},
	Volume = {5},
	Year = {2011},
	Bdsk-Url-1 = {http://dx.doi.org/10.1007/s11568-011-9155-4}}

@article{Koehler2014,
	Abstract = {The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org,
	provides a structured, comprehensive and well-defined set of 10,088
	classes (terms) describing human phenotypic abnormalities and 13,326
	subclass relations between the HPO classes. In addition we have developed
	logical definitions for 46\% of all HPO classes using terms from
	ontologies for anatomy, cell types, function, embryology, pathology
	and other domains. This allows interoperability with several resources,
	especially those containing phenotype information on model organisms
	such as mouse and zebrafish. Here we describe the updated HPO database,
	which provides annotations of 7,278 human hereditary syndromes listed
	in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes
	such as frequency, references and negations are associated with each
	annotation. Several large-scale projects worldwide utilize the HPO
	for describing phenotype information in their datasets. We have therefore
	generated equivalence mappings to other phenotype vocabularies such
	as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration
	of existing datasets and interoperability with multiple biomedical
	resources. We have created various ways to access the HPO database
	content using flat files, a MySQL database, and Web-based tools.
	All data and documentation on the HPO project can be found online.},
	Author = {K{\"{o}}hler, Sebastian and Doelken, Sandra C. and Mungall, Christopher J. and Bauer, Sebastian and Firth, Helen V. and Bailleul-Forestier, Isabelle and Black, Graeme C M. and Brown, Danielle L. and Brudno, Michael and Campbell, Jennifer and FitzPatrick, David R. and Eppig, Janan T. and Jackson, Andrew P. and Freson, Kathleen and Girdea, Marta and Helbig, Ingo and Hurst, Jane A. and J{\"{a}}hn, Johanna and Jackson, Laird G. and Kelly, Anne M. and Ledbetter, David H. and Mansour, Sahar and Martin, Christa L. and Moss, Celia and Mumford, Andrew and Ouwehand, Willem H. and Park, Soo-Mi and Riggs, Erin Rooney and Scott, Richard H. and Sisodiya, Sanjay and {Van Vooren}, Steven and Wapner, Ronald J. and Wilkie, Andrew O M. and Wright, Caroline F. and {Vulto-van Silfhout}, Anneke T. and {de Leeuw}, Nicole and {de Vries}, Bert B A. and Washingthon, Nicole L. and Smith, Cynthia L. and Westerfield, Monte and Schofield, Paul and Ruef, Barbara J. and Gkoutos, Georgios V. and Haendel, Melissa and Smedley, Damian and Lewis, Suzanna E. and Robinson, Peter N.},
	Doi = {10.1093/nar/gkt1026},
	Institution = {Institute for Medical Genetics and Human Genetics, Charit\E9-Universit\E4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany, Berlin-Brandenburg Center for Regenerative Therapies, Charit\E9-Universit\E4tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany, Lawrence Berkeley National Laboratory, Mail Stop 84R0171, Berkeley, CA 94720, USA, The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, Department of Medical Genetics, Cambridge University Addenbrooke's Hospital, Cambridge CB2 2QQ, UK, Universit\E9 Paul Sabatier, Facult\E9 de Chirurgie Dentaire, CHU Toulouse, France, Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Sciences Centre (MAHSC), Manchester, UK, Centre for Genomic Medicine, Institute of Human Development, Faculty of Medical and Human Sciences, University of Manchester, MAHSC, Manchester M13 9WL, UK, Institute of Genetic Medicine. Newcastle University, Central Parkway, Newcastle upon Tyne, NE1 3BZ, UK, Department of Computer Science, University of Toronto, Ontario, Canada, Centre for Computational Medicine, Hospital for Sick Children, Toronto, Ontario, Canada, Department of Clinical Genetics, Leeds Teaching Hospitals NHS Trust, Leeds LS2 9NS, UK, MRC Human Genetics Unit, MRC Institute of Genetic and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK, The Jackson Laboratory, Bar Harbor, ME 04609, USA, Center for Molecular and Vascular Biology, University of Leuven, Belgium, Department of Neuropediatrics, University Medical Center Schleswig-Holstein, Kiel Campus, 24105 Kiel, Germany, NE Thames Genetics Service, Great Ormond Street Hospital, London WC1N 3JH, UK, Drexel University College of Medicine, Philadelphia, PA 19102, USA, Department of Haematology, University of Cambridge and NHS Blood and Transplant Cambridge, CB2 0PT Cambridge, UK, Autism and Developmental Medicine Institute, Geisinger Health System},
	Journal = {Nucleic Acids Res},
	Keywords = {Animals; Biological Ontologies; Databases, Factual; Genetic Diseases, Inborn, diagnosis/genetics; Genomics; Humans; Internet; Mice; Phenotype},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {Database issue},
	Owner = {peter},
	Pages = {D966--D974},
	Pii = {gkt1026},
	Pmid = {24217912},
	Timestamp = {2015.09.23},
	Title = {The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data.},
	Url = {http://dx.doi.org/10.1093/nar/gkt1026},
	Volume = {42},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gkt1026}}

@article{Koehler2014a,
	Abstract = {Clinical evaluation of CNVs identified via techniques such as array
	comparative genome hybridisation (aCGH) involves the inspection of
	lists of known and unknown duplications and deletions with the goal
	of distinguishing pathogenic from benign CNVs. A key step in this
	process is the comparison of the individual's phenotypic abnormalities
	with those associated with Mendelian disorders of the genes affected
	by the CNV. However, because often there is not much known about
	these human genes, an additional source of data that could be used
	is model organism phenotype data. Currently, almost 6000 genes in
	mouse and zebrafish are, when knocked out, associated with a phenotype
	in the model organism, but no disease is known to be caused by mutations
	in the human ortholog. Yet, searching model organism databases and
	comparing model organism phenotypes with patient phenotypes for identifying
	novel disease genes and medical evaluation of CNVs is hindered by
	the difficulty in integrating phenotype information across species
	and the lack of appropriate software tools.Here, we present an integrated
	ranking scheme based on phenotypic matching, degree of overlap with
	known benign or pathogenic CNVs and the haploinsufficiency score
	for the prioritisation of CNVs responsible for a patient's clinical
	findings.We show that this scheme leads to significant improvements
	compared with rankings that do not exploit phenotypic information.
	We provide a software tool called PhenogramViz, which supports phenotype-driven
	interpretation of aCGH findings based on multiple data sources, including
	the integrated cross-species phenotype ontology Uberpheno, in order
	to visualise gene-to-phenotype relations.Integrating and visualising
	cross-species phenotype information on the affected genes may help
	in routine diagnostics of CNVs.},
	Author = {K\"{o}hler, Sebastian and Schoeneberg, Uwe and Czeschik, Johanna Christina and Doelken, Sandra C and Hehir-Kwa, Jayne Y and Ibn-Salem, Jonas and Mungall, Christopher J and Smedley, Damian and Haendel, Melissa A and Robinson, Peter N},
	Doi = {10.1136/jmedgenet-2014-102633},
	Institution = {Institute for Medical Genetics and Human Genetics, Charit�-Universit�tsmedizin Berlin, Berlin, Germany Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany Max Planck Institute for Molecular Genetics, Berlin, Germany Department of},
	Journal = {J Med Genet},
	Keywords = {Animals; Computational Biology; DNA Copy Number Va,Genetic; Disease,genetics/physiology; Databases,genetics; Humans; Mice; Phenotype; Species Specif},
	Month = nov,
	Number = {11},
	Pages = {766--772},
	Pmid = {25280750},
	Title = {{Clinical interpretation of \{CNVs\} with cross-species phenotype data.}},
	Url = {http://dx.doi.org/10.1136/jmedgenet-2014-102633},
	Volume = {51},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1136/jmedgenet-2014-102633}}

@article{Karolchik2004,
	Abstract = {The University of California Santa Cruz (UCSC) Table Browser (http://genome.ucsc.edu/cgi-bin/hgText)
	provides text-based access to a large collection of genome assemblies
	and annotation data stored in the Genome Browser Database. A flexible
	alternative to the graphical-based Genome Browser, this tool offers
	an enhanced level of query support that includes restrictions based
	on field values, free-form SQL queries and combined queries on multiple
	tables. Output can be filtered to restrict the fields and lines returned,
	and may be organized into one of several formats, including a simple
	tab- delimited file that can be loaded into a spreadsheet or database
	as well as advanced formats that may be uploaded into the Genome
	Browser as custom annotation tracks. The Table Browser User's Guide
	located on the UCSC website provides instructions and detailed examples
	for constructing queries and configuring output.},
	Author = {Karolchik, Donna and Hinrichs, Angela S and Furey, Terrence S and Roskin, Krishna M and Sugnet, Charles W and Haussler, David and Kent, W James},
	Doi = {10.1093/nar/gkh103},
	Issn = {1362-4962},
	Journal = {Nucleic acids research},
	Keywords = {Animals,Computational Biology,Databases, Genetic,Genome,Genomics,Humans,Information Storage and Retrieval,Internet,Software,User-Computer Interface},
	Month = jan,
	Number = {Database issue},
	Pages = {D493--6},
	Pmid = {14681465},
	Title = {{The UCSC Table Browser data retrieval tool.}},
	Url = {http://nar.oxfordjournals.org/content/32/suppl\_1/D493.abstract?ijkey=06tIQcBr2VZNz\&keytype=ref},
	Volume = {32},
	Year = {2004},
	Bdsk-Url-1 = {http://nar.oxfordjournals.org/content/32/suppl%5C_1/D493.abstract?ijkey=06tIQcBr2VZNz%5C&keytype=ref},
	Bdsk-Url-2 = {http://dx.doi.org/10.1093/nar/gkh103}}

@article{Kawahara2014,
	Abstract = {The human genome harbors approximately 2000 genes that encode microRNAs
	(miRNAs), small non-coding RNAs of approximately 20-22 nt that mediate
	post-transcriptional gene silencing. MiRNAs are generated from long
	transcripts through stepwise processing by the Drosha/DGCR8, Exportin-5/RanGTP
	and Dicer/TRBP complexes. Given that the expression of each individual
	miRNA is tightly regulated, the altered expression of certain miRNAs
	plays a pivotal role in human diseases. For instance, germline and
	somatic mutations in the genes encoding the miRNA processing machinery
	have been reported in different cancers. Furthermore, certain miRNA
	genes are encoded within regions that are deleted or duplicated in
	individuals with chromosomal abnormalities, and the fact that the
	knockout of these miRNAs in animal models results in lethality or
	the abnormal development of certain tissues indicates that these
	miRNA genes contribute to the disease phenotypes. It has also been
	reported that mutations in miRNA genes or in miRNA-binding sites,
	which result in the impairment of tight regulation of target mRNA
	expression, cause human genetic diseases, although these cases are
	rare. This is in contrast to the aberrant expression of certain miRNAs
	that results from the impairment of transcriptional or post-transcriptional
	regulation, which has been reported frequently in various human diseases.
	The present review focuses on human diseases caused by mutations
	in genes encoding miRNAs and the miRNA processing machinery as well
	as in miRNA-binding sites. Furthermore, human diseases caused by
	chromosomal abnormalities that involve the deletion or duplication
	of regions harboring genes that encode miRNAs or the miRNA processing
	machinery are also introduced.},
	Author = {Kawahara, Yukio},
	Doi = {10.1111/cga.12043},
	Institution = {Laboratory of RNA Function, Graduate School of Medicine, Osaka University, Suita, Osaka, Japan.},
	Journal = {Congenit Anom (Kyoto)},
	Keywords = {Animals; Chromosome Aberrations; Disease Models, Animal; Gene Expression Regulation; Genetic Diseases, Inborn, etiology/genetics/pathology; Germ Cells, pathology; Humans; MicroRNAs, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Feb},
	Number = {1},
	Owner = {peter},
	Pages = {12--21},
	Pmid = {24330020},
	Timestamp = {2015.08.09},
	Title = {Human diseases caused by germline and somatic abnormalities in microRNA and microRNA-related genes.},
	Url = {http://dx.doi.org/10.1111/cga.12043},
	Volume = {54},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1111/cga.12043}}

@article{Khan2006,
	Abstract = {DNA sequence features were sought that could be used for the in silico
	ascertainment of the likely functional consequences of single nucleotide
	changes in human gene promoter regions. To identify relevant features
	of the local DNA sequence context, we transformed into consensus
	tables the nucleotide composition of sequences flanking 101 promoter
	SNPs of type C<-->T or A<-->G, defined empirically as being either
	'functional' or 'non-functional' on the basis of a standardised reporter
	gene assay. The similarity of a given sequence to these consensus
	tables was then measured by means of the Shapiro-Senapathy score.
	A decision rule with the potential to discriminate between empirically
	ascertained functional and non-functional SNPs was proposed that
	potentiated discrimination between functional and non-functional
	SNPs with a sensitivity of 80\% and a specificity of 20\%. Two further
	datasets (viz. disease-associated SNPs of types A<-->G and C<-->T
	(N = 75) and pathological promoter mutations (transitions, N = 114))
	were retrieved from the Human Gene Mutation Database (HGMD; http://www.hgmd.org/)
	and analyzed using consensus tables derived from the functional and
	non-functional promoter SNPs; approximately 70\% were correctly recognized
	as being of probable functional significance. Complexity analysis
	was also used to quantify the regularity of the local DNA sequence
	environment. Functional SNPs/mutations of type C<-->T were found
	to occur in DNA regions characterized by lower average sequence complexity
	as measured with respect to symmetric elements; complexity values
	increased gradually from functional SNPs and pathological mutations
	to functional disease-associated SNPs and non-functional SNPs. This
	may reflect the internal axial symmetry that frequently characterizes
	transcription factor binding sites.},
	Author = {Khan, Imtiaz A. and Mort, Matthew and Buckland, Paul R. and O'Donovan, Michael C. and Cooper, David N. and Chuzhanova, Nadia A.},
	Institution = {Biostatistics and Bioinformatics Unit, Cardiff University, Cardiff, CF14 4XN, UK.},
	Journal = {In Silico Biol},
	Keywords = {Algorithms; Base Sequence; Binding Sites; Databases, Nucleic Acid; Genetic Predisposition to Disease; Genome, Human; Humans; Mutation; Polymorphism, Single Nucleotide; Promoter Regions, Genetic; Sequence Analysis, DNA, methods; Transcription Factors, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Number = {1-2},
	Owner = {peter},
	Pages = {23--34},
	Pii = {2006060003},
	Pmid = {16789908},
	Timestamp = {2015.07.25},
	Title = {In silico discrimination of single nucleotide polymorphisms and pathological mutations in human gene promoter regions by means of local DNA sequence context and regularity.},
	Volume = {6},
	Year = {2006}}

@article{Khurana2013,
	Abstract = {Interpreting variants, especially noncoding ones, in the increasing
	number of personal genomes is challenging. We used patterns of polymorphisms
	in functionally annotated regions in 1092 humans to identify deleterious
	variants; then we experimentally validated candidates. We analyzed
	both coding and noncoding regions, with the former corroborating
	the latter. We found regions particularly sensitive to mutations
	("ultrasensitive") and variants that are disruptive because of mechanistic
	effects on transcription-factor binding (that is, "motif-breakers").
	We also found variants in regions with higher network centrality
	tend to be deleterious. Insertions and deletions followed a similar
	pattern to single-nucleotide variants, with some notable exceptions
	(e.g., certain deletions and enhancers). On the basis of these patterns,
	we developed a computational tool (FunSeq), whose application to
	~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.},
	Author = {Khurana, Ekta and Fu, Yao and Colonna, Vincenza and Mu, Xinmeng Jasmine and Kang, Hyun Min and Lappalainen, Tuuli and Sboner, Andrea and Lochovsky, Lucas and Chen, Jieming and Harmanci, Arif and Das, Jishnu and Abyzov, Alexej and Balasubramanian, Suganthi and Beal, Kathryn and Chakravarty, Dimple and Challis, Daniel and Chen, Yuan and Clarke, Declan and Clarke, Laura and Cunningham, Fiona and Evani, Uday S. and Flicek, Paul and Fragoza, Robert and Garrison, Erik and Gibbs, Richard and G{\"{u}}m{\"{u}}s, Zeynep H. and Herrero, Javier and Kitabayashi, Naoki and Kong, Yong and Lage, Kasper and Liluashvili, Vaja and Lipkin, Steven M. and MacArthur, Daniel G. and Marth, Gabor and Muzny, Donna and Pers, Tune H. and Ritchie, Graham R S. and Rosenfeld, Jeffrey A. and Sisu, Cristina and Wei, Xiaomu and Wilson, Michael and Xue, Yali and Yu, Fuli and , 1000 Genomes Project Consortium and Dermitzakis, Emmanouil T. and Yu, Haiyuan and Rubin, Mark A. and Tyler-Smith, Chris and Gerstein, Mark},
	Doi = {10.1126/science.1235587},
	Institution = {Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.},
	Journal = {Science},
	Keywords = {Binding Sites, genetics; Genetic Variation; Genome, Human; Genomics; Humans; Kruppel-Like Transcription Factors, metabolism; Molecular Sequence Annotation, methods; Mutation; Neoplasms, genetics; Polymorphism, Single Nucleotide; Population, genetics; RNA, Untranslated, genetics; Selection, Genetic},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Oct},
	Number = {6154},
	Owner = {peter},
	Pages = {1235587},
	Pii = {342/6154/1235587},
	Pmid = {24092746},
	Timestamp = {2015.09.27},
	Title = {Integrative annotation of variants from 1092 humans: application to cancer genomics.},
	Url = {http://dx.doi.org/10.1126/science.1235587},
	Volume = {342},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1126/science.1235587}}

@article{Kircher2014,
	Abstract = {Current methods for annotating and interpreting human genetic variation
	tend to exploit a single information type (for example, conservation)
	and/or are restricted in scope (for example, to missense changes).
	Here we describe Combined Annotation-Dependent Depletion (CADD),
	a method for objectively integrating many diverse annotations into
	a single measure (C score) for each variant. We implement CADD as
	a support vector machine trained to differentiate 14.7 million high-frequency
	human-derived alleles from 14.7 million simulated variants. We precompute
	C scores for all 8.6 billion possible human single-nucleotide variants
	and enable scoring of short insertions-deletions. C scores correlate
	with allelic diversity, annotations of functionality, pathogenicity,
	disease severity, experimentally measured regulatory effects and
	complex trait associations, and they highly rank known pathogenic
	variants within individual genomes. The ability of CADD to prioritize
	functional, deleterious and pathogenic variants across many functional
	categories, effect sizes and genetic architectures is unmatched by
	any current single-annotation method.},
	Author = {Kircher, Martin and Witten, Daniela M. and Jain, Preti and O'Roak, Brian J. and Cooper, Gregory M. and Shendure, Jay},
	Institution = {Department of Genome Sciences, University of Washington, Seattle, Washington, USA.},
	Journal = {Nat Genet},
	Keywords = {Genetic Variation; Genome, Human; Genome-Wide Association Study; Humans; INDEL Mutation; Models, Genetic; Molecular Sequence Annotation; Polymorphism, Single Nucleotide; Selection, Genetic; Support Vector Machines},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Mar},
	Number = {3},
	Owner = {peter},
	Pages = {310--315},
	Pii = {ng.2892},
	Pmid = {24487276},
	Timestamp = {2015.05.24},
	Title = {A general framework for estimating the relative pathogenicity of human genetic variants.},
	Volume = {46},
	Year = {2014}}

@inbook{Kuncheva14,
	Author = {Kuncheva, Ludmila I.},
	Booktitle = {Combining Pattern Classifiers},
	Doi = {10.1002/9781118914564.ch8},
	Keywords = {classifier ensembles, ensemble diversity},
	Pages = {247--289},
	Publisher = {John Wiley \& Sons, Inc.},
	Title = {Diversity in Classifier Ensembles},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/9781118914564.ch8}}
	
@BOOK{Kun14a,
   author = "Kuncheva, L.I.",
   title = "Combining {P}attern {C}lassifiers: {Methods} and {A}lgorithms, 2nd edition",
   publisher = "Wiley-Interscience",
   address = "New York",
   year = 2014 }

@article{Landrum2014,
	Abstract = {ClinVar (http://www.ncbi.nlm.nih.gov/clinvar/) provides a freely available
	archive of reports of relationships among medically important variants
	and phenotypes. ClinVar accessions submissions reporting human variation,
	interpretations of the relationship of that variation to human health
	and the evidence supporting each interpretation. The database is
	tightly coupled with dbSNP and dbVar, which maintain information
	about the location of variation on human assemblies. ClinVar is also
	based on the phenotypic descriptions maintained in MedGen (http://www.ncbi.nlm.nih.gov/medgen).
	Each ClinVar record represents the submitter, the variation and the
	phenotype, i.e. the unit that is assigned an accession of the format
	SCV000000000.0. The submitter can update the submission at any time,
	in which case a new version is assigned. To facilitate evaluation
	of the medical importance of each variant, ClinVar aggregates submissions
	with the same variation/phenotype combination, adds value from other
	NCBI databases, assigns a distinct accession of the format RCV000000000.0
	and reports if there are conflicting clinical interpretations. Data
	in ClinVar are available in multiple formats, including html, download
	as XML, VCF or tab-delimited subsets. Data from ClinVar are provided
	as annotation tracks on genomic RefSeqs and are used in tools such
	as Variation Reporter (http://www.ncbi.nlm.nih.gov/variation/tools/reporter),
	which reports what is known about variation based on user-supplied
	locations.},
	Author = {Landrum, Melissa J. and Lee, Jennifer M. and Riley, George R. and Jang, Wonhee and Rubinstein, Wendy S. and Church, Deanna M. and Maglott, Donna R.},
	Doi = {10.1093/nar/gkt1113},
	Institution = {National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA.},
	Journal = {Nucleic Acids Res},
	Keywords = {Databases, Genetic; Genetic Variation; Genome, Human; Genomics; Humans; Internet; Phenotype},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {Database issue},
	Owner = {peter},
	Pages = {D980--D985},
	Pii = {gkt1113},
	Pmid = {24234437},
	Timestamp = {2015.08.13},
	Title = {{ClinVar}: public archive of relationships among sequence variation and human phenotype.},
	Url = {http://dx.doi.org/10.1093/nar/gkt1113},
	Volume = {42},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gkt1113}}

@article{Lappalainen2013,
	Abstract = {Much has changed in the last two years at DGVa (http://www.ebi.ac.uk/dgva)
	and dbVar (http://www.ncbi.nlm.nih.gov/dbvar). We are now processing
	direct submissions rather than only curating data from the literature
	and our joint study catalog includes data from over 100 studies in
	11 organisms. Studies from human dominate with data from control
	and case populations, tumor samples as well as three large curated
	studies derived from multiple sources. During the processing of these
	data, we have made improvements to our data model, submission process
	and data representation. Additionally, we have made significant improvements
	in providing access to these data via web and FTP interfaces.},
	Author = {Lappalainen, Ilkka and Lopez, John and Skipper, Lisa and Hefferon, Timothy and Spalding, J Dylan and Garner, John and Chen, Chao and Maguire, Michael and Corbett, Matt and Zhou, George and Paschall, Justin and Ananiev, Victor and Flicek, Paul and Church, Deanna M.},
	Doi = {10.1093/nar/gks1213},
	Institution = {European Bioinformatics Institute, Hinxton, CB10 1SD Cambridgeshire, UK.},
	Journal = {Nucleic Acids Res},
	Keywords = {Databases, Nucleic Acid; Genomic Structural Variation; Genotype; Humans; Internet; Phenotype},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {Database issue},
	Owner = {peter},
	Pages = {D936--D941},
	Pii = {gks1213},
	Pmid = {23193291},
	Timestamp = {2015.09.29},
	Title = {DbVar and DGVa: public archives for genomic structural variation.},
	Url = {http://dx.doi.org/10.1093/nar/gks1213},
	Volume = {41},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gks1213}}

@article{Lee2015,
	Abstract = {Most variants implicated in common human disease by genome-wide association
	studies (GWAS) lie in noncoding sequence intervals. Despite the suggestion
	that regulatory element disruption represents a common theme, identifying
	causal risk variants within implicated genomic regions remains a
	major challenge. Here we present a new sequence-based computational
	method to predict the effect of regulatory variation, using a classifier
	(gkm-SVM) that encodes cell type-specific regulatory sequence vocabularies.
	The induced change in the gkm-SVM score, deltaSVM, quantifies the
	effect of variants. We show that deltaSVM accurately predicts the
	impact of SNPs on DNase I sensitivity in their native genomic contexts
	and accurately predicts the results of dense mutagenesis of several
	enhancers in reporter assays. Previously validated GWAS SNPs yield
	large deltaSVM scores, and we predict new risk-conferring SNPs for
	several autoimmune diseases. Thus, deltaSVM provides a powerful computational
	approach to systematically identify functional regulatory variants.},
	Author = {Lee, Dongwon and Gorkin, David U. and Baker, Maggie and Strober, Benjamin J. and Asoni, Alessandro L. and McCallion, Andrew S. and Beer, Michael A.},
	Doi = {10.1038/ng.3331},
	Institution = {Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.},
	Journal = {Nat Genet},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Aug},
	Number = {8},
	Owner = {peter},
	Pages = {955--961},
	Pii = {ng.3331},
	Pmid = {26075791},
	Timestamp = {2015.08.09},
	Title = {A method to predict the impact of regulatory variants from DNA sequence.},
	Url = {http://dx.doi.org/10.1038/ng.3331},
	Volume = {47},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/ng.3331}}

@article{Lee2014,
	Abstract = {Clinical exome sequencing (CES) is rapidly becoming a common molecular
	diagnostic test for individuals with rare genetic disorders.To report
	on initial clinical indications for CES referrals and molecular diagnostic
	rates for different indications and for different test types.Clinical
	exome sequencing was performed on 814 consecutive patients with undiagnosed,
	suspected genetic conditions at the University of California, Los
	Angeles, Clinical Genomics Center between January 2012 and August
	2014. Clinical exome sequencing was conducted as trio-CES (both parents
	and their affected child sequenced simultaneously) to effectively
	detect de novo and compound heterozygous variants or as proband-CES
	(only the affected individual sequenced) when parental samples were
	not available.Clinical indications for CES requests, molecular diagnostic
	rates of CES overall and for phenotypic subgroups, and differences
	in molecular diagnostic rates between trio-CES and proband-CES.Of
	the 814 cases, the overall molecular diagnosis rate was 26\% (213
	of 814; 95\% CI, 23\%-29\%). The molecular diagnosis rate for trio-CES
	was 31\% (127 of 410 cases; 95\% CI, 27\%-36\%) and 22\% (74 of 338
	cases; 95\% CI, 18\%-27\%) for proband-CES. In cases of developmental
	delay in children (<5 years, n = 138), the molecular diagnosis rate
	was 41\% (45 of 109; 95\% CI, 32\%-51\%) for trio-CES cases and 9\%
	(2 of 23, 95\% CI, 1\%-28\%) for proband-CES cases. The significantly
	higher diagnostic yield (P value =?.002; odds ratio, 7.4 [95\% CI,
	1.6-33.1]) of trio-CES was due to the identification of de novo and
	compound heterozygous variants.In this sample of patients with undiagnosed,
	suspected genetic conditions, trio-CES was associated with higher
	molecular diagnostic yield than proband-CES or traditional molecular
	diagnostic methods. Additional studies designed to validate these
	findings and to explore the effect of this approach on clinical and
	economic outcomes are warranted.},
	Author = {Lee, Hane and Deignan, Joshua L. and Dorrani, Naghmeh and Strom, Samuel P. and Kantarci, Sibel and Quintero-Rivera, Fabiola and Das, Kingshuk and Toy, Traci and Harry, Bret and Yourshaw, Michael and Fox, Michelle and Fogel, Brent L. and Martinez-Agosto, Julian A. and Wong, Derek A. and Chang, Vivian Y. and Shieh, Perry B. and Palmer, Christina G S. and Dipple, Katrina M. and Grody, Wayne W. and Vilain, Eric and Nelson, Stanley F.},
	Doi = {10.1001/jama.2014.14604},
	Institution = {Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles2Clinical Genomics Center, David Geffen School of Medicine, University of California, Los Angeles6Department of Human Genetics, David Ge.},
	Journal = {JAMA},
	Keywords = {Adolescent; Adult; Child; Child, Preschool; Developmental Disabilities, genetics; Exome; Female; Genetic Diseases, Inborn, diagnosis; Humans; Infant; Infant, Newborn; Male; Molecular Diagnostic Techniques; Mutation; Rare Diseases, diagnosis/genetics; Sequence Analysis, DNA, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Nov},
	Number = {18},
	Owner = {peter},
	Pages = {1880--1887},
	Pii = {1918775},
	Pmid = {25326637},
	Timestamp = {2015.08.05},
	Title = {Clinical exome sequencing for genetic identification of rare Mendelian disorders.},
	Url = {http://dx.doi.org/10.1001/jama.2014.14604},
	Volume = {312},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1001/jama.2014.14604}}

@article{Liu09,
	Author = {Liu, X. and Wu, J. and Zhou, Z.},
	Journal = {Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on},
	Month = {April},
	Number = {2},
	Pages = {539-550},
	Title = {Exploratory Undersampling for Class-Imbalance Learning},
	Volume = {39},
	Year = {2009}}

@article{Lupski2010,
	Abstract = {Whole-genome sequencing may revolutionize medical diagnostics through
	rapid identification of alleles that cause disease. However, even
	in cases with simple patterns of inheritance and unambiguous diagnoses,
	the relationship between disease phenotypes and their corresponding
	genetic changes can be complicated. Comprehensive diagnostic assays
	must therefore identify all possible DNA changes in each haplotype
	and determine which are responsible for the underlying disorder.
	The high number of rare, heterogeneous mutations present in all humans
	and the paucity of known functional variants in more than 90\% of
	annotated genes make this challenge particularly difficult. Thus,
	the identification of the molecular basis of a genetic disease by
	means of whole-genome sequencing has remained elusive. We therefore
	aimed to assess the usefulness of human whole-genome sequencing for
	genetic diagnosis in a patient with Charcot-Marie-Tooth disease.We
	identified a family with a recessive form of Charcot-Marie-Tooth
	disease for which the genetic basis had not been identified. We sequenced
	the whole genome of the proband, identified all potential functional
	variants in genes likely to be related to the disease, and genotyped
	these variants in the affected family members.We identified and validated
	compound, heterozygous, causative alleles in SH3TC2 (the SH3 domain
	and tetratricopeptide repeats 2 gene), involving two mutations, in
	the proband and in family members affected by Charcot-Marie-Tooth
	disease. Separate subclinical phenotypes segregated independently
	with each of the two mutations; heterozygous mutations confer susceptibility
	to neuropathy, including the carpal tunnel syndrome.As shown in this
	study of a family with Charcot-Marie-Tooth disease, whole-genome
	sequencing can identify clinically relevant variants and provide
	diagnostic information to inform the care of patients.},
	Author = {Lupski, James R. and Reid, Jeffrey G. and Gonzaga-Jauregui, Claudia and {Rio Deiros}, David and Chen, David C Y. and Nazareth, Lynne and Bainbridge, Matthew and Dinh, Huyen and Jing, Chyn and Wheeler, David A. and McGuire, Amy L. and Zhang, Feng and Stankiewicz, Pawel and Halperin, John J. and Yang, Chengyong and Gehman, Curtis and Guo, Danwei and Irikat, Rola K. and Tom, Warren and Fantin, Nick J. and Muzny, Donna M. and Gibbs, Richard A.},
	Doi = {10.1056/NEJMoa0908094},
	Institution = {Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.},
	Journal = {N Engl J Med},
	Keywords = {Adult; Aged; Aged, 80 and over; Charcot-Marie-Tooth Disease, genetics; Codon, Nonsense; Female; Genes, Recessive; Genetic Association Studies; Genome, Human; Genotype; Humans; Male; Middle Aged; Mutation, Missense; Pedigree; Phenotype; Polymorphism, Single Nucleotide; Sequence Analysis, DNA},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Apr},
	Number = {13},
	Owner = {peter},
	Pages = {1181--1191},
	Pii = {NEJMoa0908094},
	Pmid = {20220177},
	Timestamp = {2015.08.05},
	Title = {Whole-genome sequencing in a patient with {Charcot-Marie-Tooth} neuropathy.},
	Url = {http://dx.doi.org/10.1056/NEJMoa0908094},
	Volume = {362},
	Year = {2010},
	Bdsk-Url-1 = {http://dx.doi.org/10.1056/NEJMoa0908094}}

@article{Ma2015,
	Abstract = {The invention of high throughput sequencing technologies has led to
	the discoveries of hundreds of thousands of genetic variants associated
	with thousands of human diseases. Many of these genetic variants
	are located outside the protein coding regions, and as such, it is
	challenging to interpret the function of these genetic variants by
	traditional genetic approaches. Recent genome-wide functional genomics
	studies, such as FANTOM5 and ENCODE have uncovered a large number
	of regulatory elements across hundreds of different tissues or cell
	lines in the human genome. These findings provide an opportunity
	to study the interaction between regulatory elements and disease-associated
	genetic variants. Identifying these diseased-related regulatory elements
	will shed light on understanding the mechanisms of how these variants
	regulate gene expression and ultimately result in disease formation
	and progression.In this study, we curated and categorized 27,558
	Mendelian disease variants, 20,964 complex disease variants, 5,809
	cancer predisposing germline variants, and 43,364 recurrent cancer
	somatic mutations. Compared against nine different types of regulatory
	regions from FANTOM5 and ENCODE projects, we found that different
	types of disease variants show distinctive propensity for particular
	regulatory elements. Mendelian disease variants and recurrent cancer
	somatic mutations are 22-fold and 10- fold significantly enriched
	in promoter regions respectively (q<0.001), compared with allele-frequency-matched
	genomic background. Separate from these two categories, cancer predisposing
	germline variants are 27-fold enriched in histone modification regions
	(q<0.001), 10-fold enriched in chromatin physical interaction regions
	(q<0.001), and 6-fold enriched in transcription promoters (q<0.001).
	Furthermore, Mendelian disease variants and recurrent cancer somatic
	mutations share very similar distribution across types of functional
	effects.Disease-associated variants in different disease categories
	are preferentially located in particular regulatory elements. These
	results will be useful for an overall understanding about the differences
	among the pathogenic mechanisms of various disease-associated variants.},
	Author = {Ma, Meng and Ru, Ying and Chuang, Ling-Shiang and Hsu, Nai-Yun and Shi, Li-Song and Hakenberg, J{\"{o}}rg and Cheng, Wei-Yi and Uzilov, Andrew and Ding, Wei and Glicksberg, Benjamin S. and Chen, Rong},
	Doi = {10.1186/1471-2164-16-S8-S3},
	Journal = {BMC Genomics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Owner = {peter},
	Pages = {S3},
	Pii = {1471-2164-16-S8-S3},
	Pmid = {26110593},
	Timestamp = {2015.08.06},
	Title = {Disease-associated variants in different categories of disease located in distinct regulatory elements.},
	Url = {http://dx.doi.org/10.1186/1471-2164-16-S8-S3},
	Volume = {16 Suppl 8},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/1471-2164-16-S8-S3}}

@article{MacDonald2014,
	Abstract = {Over the past decade, the Database of Genomic Variants (DGV; http://dgv.tcag.ca/)
	has provided a publicly accessible, comprehensive curated catalogue
	of structural variation (SV) found in the genomes of control individuals
	from worldwide populations. Here, we describe updates and new features,
	which have expanded the utility of DGV for both the basic research
	and clinical diagnostic communities. The current version of DGV consists
	of 55 published studies, comprising >2.5 million entries identified
	in >22,300 genomes. Studies included in DGV are selected from the
	accessioned data sets in the archival SV databases dbVar (NCBI) and
	DGVa (EBI), and then further curated for accuracy and validity. The
	core visualization tool (gbrowse) has been upgraded with additional
	functions to facilitate data analysis and comparison, and a new query
	tool has been developed to provide flexible and interactive access
	to the data. The content from DGV is regularly incorporated into
	other large-scale genome reference databases and represents a standard
	data resource for new product and database development, in particular
	for copy number variation testing in clinical labs. The accurate
	cataloguing of variants in DGV will continue to enable medical genetics
	and genome sequencing research.},
	Author = {MacDonald, Jeffrey R and Ziman, Robert and Yuen, Ryan K C and Feuk, Lars and Scherer, Stephen W},
	Doi = {10.1093/nar/gkt958},
	File = {:home/mschubach/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/MacDonald et al. - 2014 - The Database of Genomic Variants a curated collection of structural variation in the human genome.pdf:pdf},
	Issn = {1362-4962},
	Journal = {Nucleic acids research},
	Keywords = {Databases, Nucleic Acid,Disease,Disease: genetics,Genome, Human,Genomic Structural Variation,Humans,Internet},
	Month = jan,
	Number = {Database issue},
	Pages = {D986--92},
	Pmid = {24174537},
	Title = {{The Database of Genomic Variants: a curated collection of structural variation in the human genome.}},
	Url = {http://nar.oxfordjournals.org/content/42/D1/D986.long},
	Volume = {42},
	Year = {2014},
	Bdsk-Url-1 = {http://nar.oxfordjournals.org/content/42/D1/D986.long},
	Bdsk-Url-2 = {http://dx.doi.org/10.1093/nar/gkt958}}

@article{Masino2014,
	Abstract = {Exome sequencing is a promising method for diagnosing patients with
	a complex phenotype. However, variant interpretation relative to
	patient phenotype can be challenging in some scenarios, particularly
	clinical assessment of rare complex phenotypes. Each patient's sequence
	reveals many possibly damaging variants that must be individually
	assessed to establish clear association with patient phenotype. To
	assist interpretation, we implemented an algorithm that ranks a given
	set of genes relative to patient phenotype. The algorithm orders
	genes by the semantic similarity computed between phenotypic descriptors
	associated with each gene and those describing the patient. Phenotypic
	descriptor terms are taken from the Human Phenotype Ontology (HPO)
	and semantic similarity is derived from each term's information content.Model
	validation was performed via simulation and with clinical data. We
	simulated 33 Mendelian diseases with 100 patients per disease. We
	modeled clinical conditions by adding noise and imprecision, i.e.
	phenotypic terms unrelated to the disease and terms less specific
	than the actual disease terms. We ranked the causative gene against
	all 2488 HPO annotated genes. The median causative gene rank was
	1 for the optimal and noise cases, 12 for the imprecision case, and
	60 for the imprecision with noise case. Additionally, we examined
	a clinical cohort of subjects with hearing impairment. The disease
	gene median rank was 22. However, when also considering the patient's
	exome data and filtering non-exomic and common variants, the median
	rank improved to 3.Semantic similarity can rank a causative gene
	highly within a gene list relative to patient phenotype characteristics,
	provided that imprecision is mitigated. The clinical case results
	suggest that phenotype rank combined with variant analysis provides
	significant improvement over the individual approaches. We expect
	that this combined prioritization approach may increase accuracy
	and decrease effort for clinical genetic diagnosis.},
	Author = {Masino, Aaron J. and Dechene, Elizabeth T. and Dulik, Matthew C. and Wilkens, Alisha and Spinner, Nancy B. and Krantz, Ian D. and Pennington, Jeffrey W. and Robinson, Peter N. and White, Peter S.},
	Doi = {10.1186/1471-2105-15-248},
	Institution = {Department of Pediatrics, Cincinnati Children's Hospital and Medical Center, Cincinnati, OH, USA. peter.white@cchmc.org.},
	Journal = {BMC Bioinformatics},
	Keywords = {Algorithms; Biological Ontologies; Computational Biology, methods; Data Mining, methods; Databases, Genetic; Disease, genetics; Exome, genetics; Humans; Phenotype; Semantics; Software},
	Language = {eng},
	Medline-Pst = {epublish},
	Owner = {peter},
	Pages = {248},
	Pii = {1471-2105-15-248},
	Pmid = {25047600},
	Timestamp = {2015.08.09},
	Title = {Clinical phenotype-based gene prioritization: an initial study using semantic similarity and the human phenotype ontology.},
	Url = {http://dx.doi.org/10.1186/1471-2105-15-248},
	Volume = {15},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/1471-2105-15-248}}

@article{Meola2009,
	Abstract = {microRNAs (miRNAs) are a class of small RNAs (19-25 nucleotides in
	length) processed from double-stranded hairpin precursors. They negatively
	regulate gene expression in animals, by binding, with imperfect base
	pairing, to target sites in messenger RNAs (usually in 3' untranslated
	regions) thereby either reducing translational efficiency or determining
	transcript degradation. Considering that each miRNA can regulate,
	on average, the expression of approximately several hundred target
	genes, the miRNA apparatus can participate in the control of the
	gene expression of a large quota of mammalian transcriptomes and
	proteomes. As a consequence, miRNAs are expected to regulate various
	developmental and physiological processes, such as the development
	and function of many tissue and organs. Due to the strong impact
	of miRNAs on the biological processes, it is expected that mutations
	affecting miRNA function have a pathogenic role in human genetic
	diseases, similar to protein-coding genes. In this review, we provide
	an overview of the evidence available to date which support the pathogenic
	role of miRNAs in human genetic diseases. We will first describe
	the main types of mutation mechanisms affecting miRNA function that
	can result in human genetic disorders, namely: (1) mutations affecting
	miRNA sequences; (2) mutations in the recognition sites for miRNAs
	harboured in target mRNAs; and (3) mutations in genes that participate
	in the general processes of miRNA processing and function. Finally,
	we will also describe the results of recent studies, mostly based
	on animal models, indicating the phenotypic consequences of miRNA
	alterations on the function of several tissues and organs. These
	studies suggest that the spectrum of genetic diseases possibly caused
	by mutations in miRNAs is wide and is only starting to be unravelled.},
	Author = {Meola, Nicola and Gennarino, Vincenzo Alessandro and Banfi, Sandro},
	Doi = {10.1186/1755-8417-2-7},
	Institution = {Telethon Institute of Genetics and Medicine (TIGEM), 80131 Naples, Italy. banfi@tigem.it.},
	Journal = {Pathogenetics},
	Language = {eng},
	Medline-Pst = {epublish},
	Number = {1},
	Owner = {peter},
	Pages = {7},
	Pii = {1755-8417-2-7},
	Pmid = {19889204},
	Timestamp = {2015.08.09},
	Title = {{microRNAs} and genetic diseases.},
	Url = {http://dx.doi.org/10.1186/1755-8417-2-7},
	Volume = {2},
	Year = {2009},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/1755-8417-2-7}}

@article{Miller2010,
	Abstract = {Chromosomal microarray (CMA) is increasingly utilized for genetic
	testing of individuals with unexplained developmental delay/intellectual
	disability (DD/ID), autism spectrum disorders (ASD), or multiple
	congenital anomalies (MCA). Performing CMA and G-banded karyotyping
	on every patient substantially increases the total cost of genetic
	testing. The International Standard Cytogenomic Array (ISCA) Consortium
	held two international workshops and conducted a literature review
	of 33 studies, including 21,698 patients tested by CMA. We provide
	an evidence-based summary of clinical cytogenetic testing comparing
	CMA to G-banded karyotyping with respect to technical advantages
	and limitations, diagnostic yield for various types of chromosomal
	aberrations, and issues that affect test interpretation. CMA offers
	a much higher diagnostic yield (15\%-20\%) for genetic testing of
	individuals with unexplained DD/ID, ASD, or MCA than a G-banded karyotype
	(∼3\%, excluding Down syndrome and other recognizable chromosomal
	syndromes), primarily because of its higher sensitivity for submicroscopic
	deletions and duplications. Truly balanced rearrangements and low-level
	mosaicism are generally not detectable by arrays, but these are relatively
	infrequent causes of abnormal phenotypes in this population (<1\%).
	Available evidence strongly supports the use of CMA in place of G-banded
	karyotyping as the first-tier cytogenetic diagnostic test for patients
	with DD/ID, ASD, or MCA. G-banded karyotype analysis should be reserved
	for patients with obvious chromosomal syndromes (e.g., Down syndrome),
	a family history of chromosomal rearrangement, or a history of multiple
	miscarriages. {\copyright} 2010 The American Society of Human Genetics.},
	Author = {Miller, David T. and Adam, Margaret P. and Aradhya, Swaroop and Biesecker, Leslie G. and Brothman, Arthur R. and Carter, Nigel P. and Church, Deanna M. and Crolla, John a. and Eichler, Evan E. and Epstein, Charles J. and Faucett, W. Andrew and Feuk, Lars and Friedman, Jan M. and Hamosh, Ada and Jackson, Laird and Kaminsky, Erin B. and Kok, Klaas and Krantz, Ian D. and Kuhn, Robert M. and Lee, Charles and Ostell, James M. and Rosenberg, Carla and Scherer, Stephen W. and Spinner, Nancy B. and Stavropoulos, Dimitri J. and Tepperberg, James H. and Thorland, Erik C. and Vermeesch, Joris R. and Waggoner, Darrel J. and Watson, Michael S. and Martin, Christa Lese and Ledbetter, David H.},
	Doi = {10.1016/j.ajhg.2010.04.006},
	Isbn = {1537-6605 (Electronic)$\backslash$r0002-9297 (Linking)},
	Issn = {00029297},
	Journal = {American Journal of Human Genetics},
	Keywords = {Child,Chromosome Banding,Chromosome Disorders,Chromosome Disorders: genetics,Congenital Abnormalities,Congenital Abnormalities: genetics,Developmental Disabilities,Developmental Disabilities: genetics,Humans,Karyotyping},
	Month = may,
	Number = {5},
	Pages = {749--764},
	Pmid = {20466091},
	Title = {{Consensus Statement: Chromosomal Microarray Is a First-Tier Clinical Diagnostic Test for Individuals with Developmental Disabilities or Congenital Anomalies}},
	Url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2869000\&tool=pmcentrez\&rendertype=abstract},
	Volume = {86},
	Year = {2010},
	Bdsk-Url-1 = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2869000%5C&tool=pmcentrez%5C&rendertype=abstract},
	Bdsk-Url-2 = {http://dx.doi.org/10.1016/j.ajhg.2010.04.006}}

@incollection{Parambath14,
	Author = {Parambath, S. and Usunier, N. and Grandvalet, Y.},
	Booktitle = {Advances in Neural Information Processing Systems 27},
	Editor = {Z. Ghahramani and M. Welling and C. Cortes and N.d. Lawrence and K.q. Weinberger},
	Pages = {2123--2131},
	Publisher = {Curran Associates, Inc.},
	Title = {Optimizing F-Measures by Cost-Sensitive Classification},
	Url = {http://papers.nips.cc/paper/5508-optimizing-f-measures-by-cost-sensitive-classification.pdf},
	Year = {2014},
	Bdsk-Url-1 = {http://papers.nips.cc/paper/5508-optimizing-f-measures-by-cost-sensitive-classification.pdf}}

@article{Paten2008a,
	Abstract = {Pairwise whole-genome alignment involves the creation of a homology
	map, capable of performing a near complete transformation of one
	genome into another. For multiple genomes this problem is generalized
	to finding a set of consistent homology maps for converting each
	genome in the set of aligned genomes into any of the others. The
	problem can be divided into two principal stages. First, the partitioning
	of the input genomes into a set of colinear segments, a process which
	essentially deals with the complex processes of rearrangement. Second,
	the generation of a base pair level alignment map for each colinear
	segment. We have developed a new genome-wide segmentation program,
	Enredo, which produces colinear segments from extant genomes handling
	rearrangements, including duplications. We have then applied the
	new alignment program Pecan, which makes the consistency alignment
	methodology practical at a large scale, to create a new set of genome-wide
	mammalian alignments. We test both Enredo and Pecan using novel and
	existing assessment analyses that incorporate both real biological
	data and simulations, and show that both independently and in combination
	they outperform existing programs. Alignments from our pipeline are
	publicly available within the Ensembl genome browser.},
	Author = {Paten, Benedict and Herrero, Javier and Beal, Kathryn and Fitzgerald, Stephen and Birney, Ewan},
	Doi = {10.1101/gr.076554.108},
	Institution = {Center for Biomolecular Science and Engineering, University of California, Santa Cruz, California 95064, USA. benedict@soe.ucsc.edu},
	Journal = {Genome Res},
	Keywords = {Animals; Chromosome Mapping, statistics /&/ numerical data; Chromosomes, Human, X, genetics; Computer Graphics; Computer Simulation; Databases, Genetic; Exons; Gene Duplication; Gene Rearrangement; Genomics, statistics /&/ numerical data; Humans; Mammals, genetics; Sequence Alignment, statistics /&/ numerical data; Software},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Nov},
	Number = {11},
	Owner = {peter},
	Pages = {1814--1828},
	Pii = {gr.076554.108},
	Pmid = {18849524},
	Timestamp = {2015.05.24},
	Title = {Enredo and Pecan: genome-wide mammalian consistency-based multiple alignment with paralogs.},
	Url = {http://dx.doi.org/10.1101/gr.076554.108},
	Volume = {18},
	Year = {2008},
	Bdsk-Url-1 = {http://dx.doi.org/10.1101/gr.076554.108}}

@article{Paten2008,
	Abstract = {Recently attention has been turned to the problem of reconstructing
	complete ancestral sequences from large multiple alignments. Successful
	generation of these genome-wide reconstructions will facilitate a
	greater knowledge of the events that have driven evolution. We present
	a new evolutionary alignment modeler, called "Ortheus," for inferring
	the evolutionary history of a multiple alignment, in terms of both
	substitutions and, importantly, insertions and deletions. Based on
	a multiple sequence probabilistic transducer model of the type proposed
	by Holmes, Ortheus uses efficient stochastic graph-based dynamic
	programming methods. Unlike other methods, Ortheus does not rely
	on a single fixed alignment from which to work. Ortheus is also more
	scaleable than previous methods while being fast, stable, and open
	source. Large-scale simulations show that Ortheus performs close
	to optimally on a deep mammalian phylogeny. Simulations also indicate
	that significant proportions of errors due to insertions and deletions
	can be avoided by not assuming a fixed alignment. We additionally
	use a challenging hold-out cross-validation procedure to test the
	method; using the reconstructions to predict extant sequence bases,
	we demonstrate significant improvements over using closest extant
	neighbor sequences. Accompanying this paper, a new, public, and genome-wide
	set of Ortheus ancestor alignments provide an intriguing new resource
	for evolutionary studies in mammals. As a first piece of analysis,
	we attempt to recover "fossilized" ancestral pseudogenes. We confidently
	find 31 cases in which the ancestral sequence had a more complete
	sequence than any of the extant sequences.},
	Author = {Paten, Benedict and Herrero, Javier and Fitzgerald, Stephen and Beal, Kathryn and Flicek, Paul and Holmes, Ian and Birney, Ewan},
	Doi = {10.1101/gr.076521.108},
	Institution = {Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz, California 95064, USA. benedict@soe.ucsc.edu},
	Journal = {Genome Res},
	Keywords = {Algorithms; Animals; Base Sequence; Computer Simulation; DNA, genetics; Evolution, Molecular; Fossils; Genomics, statistics /&/ numerical data; Humans; Mammals, genetics; Models, Statistical; Phylogeny; Pseudogenes; Sequence Alignment, statistics /&/ numerical data; Software; Stochastic Processes},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Nov},
	Number = {11},
	Owner = {peter},
	Pages = {1829--1843},
	Pii = {gr.076521.108},
	Pmid = {18849525},
	Timestamp = {2015.05.24},
	Title = {Genome-wide nucleotide-level mammalian ancestor reconstruction.},
	Url = {http://dx.doi.org/10.1101/gr.076521.108},
	Volume = {18},
	Year = {2008},
	Bdsk-Url-1 = {http://dx.doi.org/10.1101/gr.076521.108}}

@article{Pickering2005,
	Abstract = {Translational control is a key step in eukaryotic gene expression.
	The majority of translational control occurs at the level of initiation,
	thus implicating the 5' untranslated region as a major site of translational
	regulation. Many growth-related mRNAs have atypical 5' UTRs, which
	are often long and GC-rich. Such features promote formation of stable
	secondary structure, and many mRNAs encoding proteins involved in
	cell growth, proliferation and apoptosis have structured 5' UTRs,
	which in many cases harbour internal ribosome entry sites (IRESs)
	and upstream open-reading frames (uORFs). In this review we discuss
	how secondary structural elements in the 5' UTR can regulate translation
	and how mutations that perturb these secondary structural elements
	can have implications for disease and tumourigenesis.},
	Author = {Pickering, Becky M. and Willis, Anne E.},
	Doi = {10.1016/j.semcdb.2004.11.006},
	Institution = {Department of Biochemistry, University of Leicester, University Rd, Leicester LE17RH, UK.},
	Journal = {Semin Cell Dev Biol},
	Keywords = {5' Untranslated Regions, chemistry/physiology; Genetic Diseases, Inborn, genetics; Nucleic Acid Conformation; Protein Biosynthesis; RNA, chemistry/physiology},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Feb},
	Number = {1},
	Owner = {peter},
	Pages = {39--47},
	Pii = {S1084-9521(04)00110-7},
	Pmid = {15659338},
	Timestamp = {2015.08.04},
	Title = {The implications of structured 5' untranslated regions on translation and disease.},
	Url = {http://dx.doi.org/10.1016/j.semcdb.2004.11.006},
	Volume = {16},
	Year = {2005},
	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.semcdb.2004.11.006}}

@article{Podlevsky2008,
	Abstract = {Telomerase is a ribonucleoprotein enzyme that extends DNA at the chromosome
	ends in most eukaryotes. Since 1985, telomerase has been studied
	intensively and components of the telomerase complex have been identified
	from over 160 eukaryotic species. In the last two decades, there
	has been a growing interest in studying telomerase owing to its vital
	role in chromosome stability and cellular immortality. To keep up
	with the remarkable explosion of knowledge about telomerase, we compiled
	information related to telomerase in an exhaustive database called
	the Telomerase Database (http://telomerase.asu.edu/). The Telomerase
	Database provides comprehensive information about (i) sequences of
	the RNA and protein subunits of telomerase, (ii) sequence alignments
	based on the phylogenetic relationship and structure, (iii) secondary
	structures of the RNA component and tertiary structures of various
	subunits of telomerase, (iv) mutations of telomerase components found
	in human patients and (v) active researchers who contributed to the
	wealth of current knowledge on telomerase. The information is hierarchically
	organized by the components, i.e. the telomerase reverse transcriptase
	(TERT), telomerase RNA (TR) and other telomerase-associated proteins.
	The Telomerase Database is a useful resource especially for researchers
	who are interested in investigating the structure, function, evolution
	and medical relevance of the telomerase enzyme.},
	Author = {Podlevsky, Joshua D. and Bley, Christopher J. and Omana, Rebecca V. and Qi, Xiaodong and Chen, Julian J-L.},
	Doi = {10.1093/nar/gkm700},
	Institution = {School of Life Sciences and Department of Chemistry and Biochemistry, Arizona State University, Tempe, AZ 85287, USA.},
	Journal = {Nucleic Acids Res},
	Keywords = {Animals; Databases, Protein; Humans; Internet; Mutation; RNA, chemistry; Sequence Alignment; Sequence Analysis, Protein; Sequence Analysis, RNA; Telomerase, chemistry/genetics; User-Computer Interface},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {Database issue},
	Owner = {peter},
	Pages = {D339--D343},
	Pii = {gkm700},
	Pmid = {18073191},
	Timestamp = {2015.08.29},
	Title = {The telomerase database.},
	Url = {http://dx.doi.org/10.1093/nar/gkm700},
	Volume = {36},
	Year = {2008},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gkm700}}

@article{Pruitt2014,
	Abstract = {The National Center for Biotechnology Information (NCBI) Reference
	Sequence (RefSeq) database is a collection of annotated genomic,
	transcript and protein sequence records derived from data in public
	sequence archives and from computation, curation and collaboration
	(http://www.ncbi.nlm.nih.gov/refseq/). We report here on growth of
	the mammalian and human subsets, changes to NCBI's eukaryotic annotation
	pipeline and modifications affecting transcript and protein records.
	Recent changes to NCBI's eukaryotic genome annotation pipeline provide
	higher throughput, and the addition of RNAseq data to the pipeline
	results in a significant expansion of the number of transcripts and
	novel exons annotated on mammalian RefSeq genomes. Recent annotation
	changes include reporting supporting evidence for transcript records,
	modification of exon feature annotation and the addition of a structured
	report of gene and sequence attributes of biological interest. We
	also describe a revised protein annotation policy for alternatively
	spliced transcripts with more divergent predicted proteins and we
	summarize the current status of the RefSeqGene project.},
	Author = {Pruitt, Kim D and Brown, Garth R and Hiatt, Susan M and Thibaud-Nissen, Fran\c{c}oise and Astashyn, Alexander and Ermolaeva, Olga and Farrell, Catherine M and Hart, Jennifer and Landrum, Melissa J and McGarvey, Kelly M and Murphy, Michael R and O'Leary, Nuala A and Pujar, Shashikant and Rajput, Bhanu and Rangwala, Sanjida H and Riddick, Lillian D and Shkeda, Andrei and Sun, Hanzhen and Tamez, Pamela and Tully, Raymond E and Wallin, Craig and Webb, David and Weber, Janet and Wu, Wendy and DiCuccio, Michael and Kitts, Paul and Maglott, Donna R and Murphy, Terence D and Ostell, James M},
	Doi = {10.1093/nar/gkt1114},
	Issn = {1362-4962},
	Journal = {Nucleic acids research},
	Keywords = {Animals,Databases, Genetic,Eukaryota,Eukaryota: genetics,Exons,Genome,Genomics,Genomics: standards,Humans,Internet,Mammals,Mammals: genetics,Molecular Sequence Annotation,Proteins,Proteins: chemistry,Proteins: genetics,RNA,RNA: chemistry,Reference Standards},
	Mendeley-Groups = {Bioinformatic/Genomiser},
	Month = jan,
	Number = {Database issue},
	Pages = {D756--63},
	Pmid = {24259432},
	Title = {{RefSeq: an update on mammalian reference sequences.}},
	Url = {http://nar.oxfordjournals.org/content/42/D1/D756.long},
	Volume = {42},
	Year = {2014},
	Bdsk-Url-1 = {http://nar.oxfordjournals.org/content/42/D1/D756.long},
	Bdsk-Url-2 = {http://dx.doi.org/10.1093/nar/gkt1114}}

@article{Rakotomamonjy08,
	Author = {Rakotomamonjy, A. and Bach, F.R. and Canu, S. and Grandvalet, Y.},
	Journal = {Journal of Machine Learning Eesearch},
	Month = {Nov},
	Pages = {2491--2521},
	Title = {SimpleMKL},
	Volume = {9},
	Year = {2008}}

@article{Rallapalli2013,
	Abstract = {Factor IX (FIX) is important in the coagulation cascade, being activated
	to FIXa on cleavage. Defects in the human F9 gene frequently lead
	to hemophilia B.To assess 1113 unique F9 mutations corresponding
	to 3721 patient entries in a new and up-to-date interactive web database
	alongside the FIXa protein structure.The mutations database was built
	using MySQL and structural analyses were based on a homology model
	for the human FIXa structure based on closely-related crystal structures.Mutations
	have been found in 336 (73\%) out of 461 residues in FIX. There were
	812 unique point mutations, 182 deletions, 54 polymorphisms, 39 insertions
	and 26 others that together comprise a total of 1113 unique variants.
	The 64 unique mild severity mutations in the mature protein with
	known circulating protein phenotypes include 15 (23\%) quantitative
	type I mutations and 41 (64\%) predominantly qualitative type II
	mutations. Inhibitors were described in 59 reports (1.6\%) corresponding
	to 25 unique mutations.The interactive database provides insights
	into mechanisms of hemophilia B. Type II mutations are deduced to
	disrupt predominantly those structural regions involved with functional
	interactions. The interactive features of the database will assist
	in making judgments about patient management.},
	Author = {Rallapalli, P. M. and Kemball-Cook, G. and Tuddenham, E. G. and Gomez, K. and Perkins, S. J.},
	Doi = {10.1111/jth.12276},
	Institution = {Division of Biosciences, Research Department of Structural and Molecular Biology, University College London, London, UK.},
	Journal = {J Thromb Haemost},
	Keywords = {Amino Acid Sequence; Blood Coagulation, genetics; Computational Biology; Crystallography, X-Ray; DNA Mutational Analysis; Databases, Genetic; Factor IX, chemistry/genetics; Factor IXa, genetics; Genetic Predisposition to Disease; Hemophilia B, blood/genetics; Humans; Models, Molecular; Molecular Sequence Data; Mutation; Phenotype; Polymorphism, Genetic; Protein Conformation; Severity of Illness Index; Structure-Activity Relationship},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jul},
	Number = {7},
	Owner = {peter},
	Pages = {1329--1340},
	Pmid = {23617593},
	Timestamp = {2015.08.28},
	Title = {An interactive mutation database for human coagulation factor IX provides novel insights into the phenotypes and genetics of hemophilia B.},
	Url = {http://dx.doi.org/10.1111/jth.12276},
	Volume = {11},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1111/jth.12276}}

@article{Riggs2012,
	Abstract = {The evidence-based review (EBR) process has been widely used to develop
	standards for medical decision-making and to explore complex clinical
	questions. This approach can be applied to genetic tests, such as
	chromosomal microarrays, in order to assist in the clinical interpretation
	of certain copy number variants (CNVs), particularly those that are
	rare, and guide array design for optimal clinical utility. To address
	these issues, the International Standards for Cytogenomic Arrays
	Consortium has established an EBR Work Group charged with building
	a framework to systematically assess the potential clinical relevance
	of CNVs throughout the genome. This group has developed a rating
	system enumerating the evidence supporting or refuting dosage sensitivity
	for individual genes and regions that considers the following criteria:
	number of causative mutations reported; patterns of inheritance;
	consistency of phenotype; evidence from large-scale case-control
	studies; mutational mechanisms; data from public genome variation
	databases; and expert consensus opinion. The system is designed to
	be dynamic in nature, with regions being reevaluated periodically
	to incorporate emerging evidence. The evidence collected will be
	displayed within a publically available database, and can be used
	in part to inform clinical laboratory CNV interpretations as well
	as to guide array design.},
	Author = {Riggs, E R and Church, D M and Hanson, K and Horner, V L and Kaminsky, E B and Kuhn, R M and Wain, K E and Williams, E S and Aradhya, S and Kearney, H M and Ledbetter, D H and South, S T and Thorland, E C and Martin, C L},
	Doi = {10.1111/j.1399-0004.2011.01818.x},
	Issn = {1399-0004},
	Journal = {Clinical genetics},
	Keywords = {DNA Copy Number Variations,DNA Copy Number Variations: genetics,Evidence-Based Medicine,Gene Dosage,Genome, Human,Humans,Phenotype},
	Month = may,
	Number = {5},
	Pages = {403--12},
	Pmid = {22097934},
	Title = {{Towards an evidence-based process for the clinical interpretation of copy number variation.}},
	Url = {http://www.ncbi.nlm.nih.gov/pubmed/22097934},
	Volume = {81},
	Year = {2012},
	Bdsk-Url-1 = {http://www.ncbi.nlm.nih.gov/pubmed/22097934},
	Bdsk-Url-2 = {http://dx.doi.org/10.1111/j.1399-0004.2011.01818.x}}

@article{Riggs2013,
	Abstract = {The 2012 International Standards for Cytogenomic Arrays (ISCA) Consortium
	Meeting, "Towards a Universal Clinical Genomic Database," was held
	in Bethesda, Maryland, May 21-22, 2012, and was attended by over
	200 individuals from around the world representing clinical genetic
	testing laboratories, clinicians, academia, industry, research, and
	regulatory agencies. The scientific program centered on expanding
	the current focus of the ISCA Consortium to include the collection
	and curation of both structural and sequence-level variation into
	a unified clinical genomics database, available to the public through
	resources such as the National Center for Biotechnology Information's
	ClinVar database. Here, we provide an overview of the conference,
	with summaries of the topics presented for discussion by over 25
	different speakers. Presentations are available online at www.iscaconsortium.org.},
	Author = {Riggs, Erin Rooney and Wain, Karen E. and Riethmaier, Darlene and Savage, Melissa and Smith-Packard, Bethanny and Kaminsky, Erin B. and Rehm, Heidi L. and Martin, Christa Lese and Ledbetter, David H. and Faucett, W Andrew},
	Doi = {10.1002/humu.22306},
	Institution = {Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA. erin.riggs@emory.edu},
	Journal = {Hum Mutat},
	Keywords = {Databases, Genetic; Genomics; Humans},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jun},
	Number = {6},
	Owner = {peter},
	Pages = {915--919},
	Pmid = {23463607},
	Timestamp = {2015.09.29},
	Title = {Towards a Universal Clinical Genomics Database: the 2012 International Standards for Cytogenomic Arrays Consortium Meeting.},
	Url = {http://dx.doi.org/10.1002/humu.22306},
	Volume = {34},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/humu.22306}}

@article{Ritchie2014,
	Abstract = {Identifying functionally relevant variants against the background
	of ubiquitous genetic variation is a major challenge in human genetics.
	For variants in protein-coding regions, our understanding of the
	genetic code and splicing allows us to identify likely candidates,
	but interpreting variants outside genic regions is more difficult.
	Here we present genome-wide annotation of variants (GWAVA), a tool
	that supports prioritization of noncoding variants by integrating
	various genomic and epigenomic annotations.},
	Author = {Ritchie, Graham R S. and Dunham, Ian and Zeggini, Eleftheria and Flicek, Paul},
	Doi = {10.1038/nmeth.2832},
	Institution = {Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK.},
	Journal = {Nat Methods},
	Keywords = {Algorithms; Computer Simulation; Genetic Variation; Humans; Molecular Sequence Annotation; Untranslated Regions, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Mar},
	Number = {3},
	Owner = {peter},
	Pages = {294--296},
	Pii = {nmeth.2832},
	Pmid = {24487584},
	Timestamp = {2015.08.06},
	Title = {Functional annotation of noncoding sequence variants.},
	Url = {http://dx.doi.org/10.1038/nmeth.2832},
	Volume = {11},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nmeth.2832}}

@article{Robinson2014,
	Abstract = {Numerous new disease-gene associations have been identified by whole-exome
	sequencing studies in the last few years. However, many cases remain
	unsolved due to the sheer number of candidate variants remaining
	after common filtering strategies such as removing low quality and
	common variants and those deemed unlikely to be pathogenic. The observation
	that each of our genomes contains about 100 genuine loss-of-function
	variants makes identification of the causative mutation problematic
	when using these strategies alone. We propose using the wealth of
	genotype to phenotype data that already exists from model organism
	studies to assess the potential impact of these exome variants. Here,
	we introduce PHenotypic Interpretation of Variants in Exomes (PHIVE),
	an algorithm that integrates the calculation of phenotype similarity
	between human diseases and genetically modified mouse models with
	evaluation of the variants according to allele frequency, pathogenicity,
	and mode of inheritance approaches in our Exomiser tool. Large-scale
	validation of PHIVE analysis using 100,000 exomes containing known
	mutations demonstrated a substantial improvement (up to 54.1-fold)
	over purely variant-based (frequency and pathogenicity) methods with
	the correct gene recalled as the top hit in up to 83\% of samples,
	corresponding to an area under the ROC curve of >95\%. We conclude
	that incorporation of phenotype data can play a vital role in translational
	bioinformatics and propose that exome sequencing projects should
	systematically capture clinical phenotypes to take advantage of the
	strategy presented here.},
	Author = {Robinson, Peter N. and K{\"{o}}hler, Sebastian and Oellrich, Anika and , Sanger Mouse Genetics Project and Wang, Kai and Mungall, Christopher J. and Lewis, Suzanna E. and Washington, Nicole and Bauer, Sebastian and Seelow, Dominik and Krawitz, Peter and Gilissen, Christian and Haendel, Melissa and Smedley, Damian},
	Doi = {10.1101/gr.160325.113},
	Institution = {Institute for Medical and Human Genetics, Charit{\'e}-Universit{\"a}tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany;},
	Journal = {Genome Res},
	Keywords = {Algorithms; Animals; Computational Biology; Databases, Genetic; Exome, genetics; Genetic Association Studies; Genetic Predisposition to Disease; Humans; Mice; Phenotype; Polymorphism, Single Nucleotide, genetics; Sequence Analysis, DNA; Software},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Feb},
	Number = {2},
	Owner = {peter},
	Pages = {340--348},
	Pii = {gr.160325.113},
	Pmid = {24162188},
	Timestamp = {2015.08.09},
	Title = {Improved exome prioritization of disease genes through cross-species phenotype comparison.},
	Url = {http://dx.doi.org/10.1101/gr.160325.113},
	Volume = {24},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1101/gr.160325.113}}

@article{Rosenbloom2015,
	Abstract = {Launched in 2001 to showcase the draft human genome assembly, the
	UCSC Genome Browser database (http://genome.ucsc.edu) and associated
	tools continue to grow, providing a comprehensive resource of genome
	assemblies and annotations to scientists and students worldwide.
	Highlights of the past year include the release of a browser for
	the first new human genome reference assembly in 4 years in December
	2013 (GRCh38, UCSC hg38), a watershed comparative genomics annotation
	(100-species multiple alignment and conservation) and a novel distribution
	mechanism for the browser (GBiB: Genome Browser in a Box). We created
	browsers for new species (Chinese hamster, elephant shark, minke
	whale), 'mined the web' for DNA sequences and expanded the browser
	display with stacked color graphs and region highlighting. As our
	user community increasingly adopts the UCSC track hub and assembly
	hub representations for sharing large-scale genomic annotation data
	sets and genome sequencing projects, our menu of public data hubs
	has tripled.},
	Author = {Rosenbloom, Kate R. and Armstrong, Joel and Barber, Galt P. and Casper, Jonathan and Clawson, Hiram and Diekhans, Mark and Dreszer, Timothy R. and Fujita, Pauline A. and Guruvadoo, Luvina and Haeussler, Maximilian and Harte, Rachel A. and Heitner, Steve and Hickey, Glenn and Hinrichs, Angie S. and Hubley, Robert and Karolchik, Donna and Learned, Katrina and Lee, Brian T. and Li, Chin H. and Miga, Karen H. and Nguyen, Ngan and Paten, Benedict and Raney, Brian J. and Smit, Arian F A. and Speir, Matthew L. and Zweig, Ann S. and Haussler, David and Kuhn, Robert M. and Kent, W James},
	Doi = {10.1093/nar/gku1177},
	Institution = {Center for Biomolecular Science and Engineering, CBSE, UC Santa Cruz, 1156 High Street, Santa Cruz, CA 95064, USA.},
	Journal = {Nucleic Acids Res},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {Database issue},
	Owner = {peter},
	Pages = {D670--D681},
	Pii = {gku1177},
	Pmid = {25428374},
	Timestamp = {2015.06.03},
	Title = {The {UCSC Genome Browser} database: 2015 update.},
	Url = {http://dx.doi.org/10.1093/nar/gku1177},
	Volume = {43},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gku1177}}

@article{Sakabe2012,
	Abstract = {Distal transcription enhancers are cis-regulatory elements that promote
	gene expression, enabling spatiotemporal control of genetic programs
	such as those required in metazoan developmental processes. Because
	of their importance, their disruption can lead to disease.},
	Author = {Sakabe, Noboru Jo and Savic, Daniel and Nobrega, Marcelo A.},
	Doi = {10.1186/gb-2012-13-1-238},
	Institution = {Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA. nsakabe@uchicago.edu},
	Journal = {Genome Biol},
	Keywords = {Cell Differentiation, genetics; Enhancer Elements, Genetic; Epigenesis, Genetic; Gene Expression Regulation, Developmental; Genome; Genome-Wide Association Study; Humans; Transcription, Genetic},
	Language = {eng},
	Medline-Pst = {epublish},
	Number = {1},
	Owner = {peter},
	Pages = {238},
	Pii = {gb-2012-13-1-238},
	Pmid = {22269347},
	Timestamp = {2015.07.09},
	Title = {Transcriptional enhancers in development and disease.},
	Url = {http://dx.doi.org/10.1186/gb-2012-13-1-238},
	Volume = {13},
	Year = {2012},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/gb-2012-13-1-238}}

@article{Savinkova2009,
	Abstract = {TATA-binding protein (TBP) is the first basal factor that recognizes
	and binds a TATA box on TATA-containing gene promoters transcribed
	by RNA polymerase II. Data available in the literature are indicative
	of admissible variability of the TATA box. The TATA box flanking
	sequences can influence TBP affinity as well as the level of basal
	and activated transcription. The possibility of mediated involvement
	in in vivo gene expression regulation of the TBP interactions with
	variant TATA boxes is supported by data on TATA box polymorphisms
	and associated human hereditary pathologies. A table containing data
	on TATA element polymorphisms in human gene promoters (about 40 mutations
	have been described), associated with particular pathologies, their
	short functional characteristics, and manifestation mechanisms of
	TATA-box SNPs is presented. Four classes of polymorphisms are considered:
	TATA box polymorphisms that weaken and enhance promoter, polymorphisms
	causing TATA box emergence and disappearance, and human virus TATA
	box polymorphisms. The described examples are indicative of the polymorphism-associated
	severe pathologies like thalassemia, the increased risk of hepatocellular
	carcinoma, sensitivity to H. pylori infection, oral cavity and lung
	cancers, arterial hypertension, etc.},
	Author = {Savinkova, L. K. and Ponomarenko, M. P. and Ponomarenko, P. M. and Drachkova, I. A. and Lysova, M. V. and Arshinova, T. V. and Kolchanov, N. A.},
	Institution = {Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia. icg-adm@bionet.nsc.ru},
	Journal = {Biochemistry (Mosc)},
	Keywords = {Genetic Diseases, Inborn, genetics; Genetic Predisposition to Disease; Humans; Mutation; Polymorphism, Single Nucleotide; Promoter Regions, Genetic; RNA Polymerase II, genetics; TATA Box; TATA-Box Binding Protein, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Feb},
	Number = {2},
	Owner = {peter},
	Pages = {117--129},
	Pii = {BCM74020149},
	Pmid = {19267666},
	Timestamp = {2015.07.09},
	Title = {{TATA} box polymorphisms in human gene promoters and associated hereditary pathologies.},
	Volume = {74},
	Year = {2009}}

@article{Scheper2007,
	Abstract = {The list of genetic diseases caused by mutations that affect mRNA
	translation is rapidly growing. Although protein synthesis is a fundamental
	process in all cells, the disease phenotypes show a surprising degree
	of heterogeneity. Studies of some of these diseases have provided
	intriguing new insights into the functions of proteins involved in
	the process of translation; for example, evidence suggests that several
	have other functions in addition to their roles in translation. Given
	the numerous proteins involved in mRNA translation, it is likely
	that further inherited diseases will turn out to be caused by mutations
	in genes that are involved in this complex process.},
	Author = {Scheper, Gert C. and {van der Knaap}, Marjo S. and Proud, Christopher G.},
	Doi = {10.1038/nrg2142},
	Institution = {Department of Child Neurology/Center for Neurogenomics and Cognitive Research, Vrije Universiteit Medical Center, De Boelelaan 1117, 1081HV Amsterdam, The Netherlands.},
	Journal = {Nat Rev Genet},
	Keywords = {5' Untranslated Regions, genetics; Animals; Gene Expression Regulation; Genetic Diseases, Inborn, genetics/metabolism; Humans; Mitochondria, genetics; Models, Biological; Mutation, physiology; Peptide Elongation Factors, genetics; Peptide Initiation Factors, genetics; Peptide Termination Factors, genetics; Protein Biosynthesis, genetics; RNA, Transfer, genetics; Ribosomes, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Sep},
	Number = {9},
	Owner = {peter},
	Pages = {711--723},
	Pii = {nrg2142},
	Pmid = {17680008},
	Timestamp = {2015.08.05},
	Title = {Translation matters: protein synthesis defects in inherited disease.},
	Url = {http://dx.doi.org/10.1038/nrg2142},
	Volume = {8},
	Year = {2007},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nrg2142}}

@article{Schwarz2014,
	Author = {Schwarz, Jana Marie and Cooper, David N. and Schuelke, Markus and Seelow, Dominik},
	Doi = {10.1038/nmeth.2890},
	Institution = {NeuroCure Clinical Research Center, Charit{\'e} - Universit{\"a}tsmedizin Berlin, Berlin, Germany.},
	Journal = {Nat Methods},
	Keywords = {Base Sequence; DNA Barcoding, Taxonomic; DNA, genetics; Mutation; Software},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Apr},
	Number = {4},
	Owner = {peter},
	Pages = {361--362},
	Pii = {nmeth.2890},
	Pmid = {24681721},
	Timestamp = {2015.08.05},
	Title = {{MutationTaster2}: mutation prediction for the deep-sequencing age.},
	Url = {http://dx.doi.org/10.1038/nmeth.2890},
	Volume = {11},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nmeth.2890}}

@article{Shihab2015,
	Abstract = {MOTIVATION: Technological advances have enabled the identification
	of an increasingly large spectrum of single nucleotide variants within
	the human genome, many of which may be associated with monogenic
	disease or complex traits. Here, we propose an integrative approach,
	named FATHMM-MKL, to predict the functional consequences of both
	coding and non-coding sequence variants. Our method utilizes various
	genomic annotations, which have recently become available, and learns
	to weight the significance of each component annotation source. RESULTS:
	We show that our method outperforms current state-of-the-art algorithms,
	CADD and GWAVA, when predicting the functional consequences of non-coding
	variants. In addition, FATHMM-MKL is comparable to the best of these
	algorithms when predicting the impact of coding variants. The method
	includes a confidence measure to rank order predictions. Availability
	and implementation: The FATHMM-MKL webserver is available at: http://fathmm.biocompute.org.uk
	CONTACT: H.Shihab@bristol.ac.uk OR : Mark.Rogers@bristol.ac.uk OR:
	C.Campbell@bristol.ac.uk Supplementary information: Supplementary
	data are available at Bioinformatics online.},
	Author = {Shihab, Hashem A and Rogers, Mark F and Gough, Julian and Mort, Matthew and Cooper, David N and Day, Ian N M and Gaunt, Tom R and Campbell, Colin},
	Doi = {10.1093/bioinformatics/btv009},
	Issn = {1367-4811},
	Journal = {Bioinformatics (Oxford, England)},
	Mendeley-Groups = {Bioinformatic/Genomics/Pathogenicity scores},
	Month = jan,
	Number = {10},
	Pages = {1536--1543},
	Pmid = {25583119},
	Title = {{An integrative approach to predicting the functional effects of non-coding and coding sequence variation.}},
	Url = {http://bioinformatics.oxfordjournals.org/content/31/10/1536.short?rss=1},
	Volume = {31},
	Year = {2015},
	Bdsk-Url-1 = {http://bioinformatics.oxfordjournals.org/content/31/10/1536.short?rss=1},
	Bdsk-Url-2 = {http://dx.doi.org/10.1093/bioinformatics/btv009}}

@inproceedings{Siepel2006,
	Author = {Siepel, A and Pollard, K and Haussler, D.},
	Booktitle = {Proceedings of the 10th international conference on research in computational molecular biology (RECOMB 2006)},
	Owner = {peter},
	Pages = {190-205},
	Timestamp = {2015.09.24},
	Title = {New methods for detecting lineage-specific selection},
	Year = {2006}}

@article{Sifrim2013,
	Abstract = {Massively parallel sequencing greatly facilitates the discovery of
	novel disease genes causing Mendelian and oligogenic disorders. However,
	many mutations are present in any individual genome, and identifying
	which ones are disease causing remains a largely open problem. We
	introduce eXtasy, an approach to prioritize nonsynonymous single-nucleotide
	variants (nSNVs) that substantially improves prediction of disease-causing
	variants in exome sequencing data by integrating variant impact prediction,
	haploinsufficiency prediction and phenotype-specific gene prioritization.},
	Author = {Sifrim, Alejandro and Popovic, Dusan and Tranchevent, Leon-Charles and Ardeshirdavani, Amin and Sakai, Ryo and Konings, Peter and Vermeesch, Joris R. and Aerts, Jan and {De Moor}, Bart and Moreau, Yves},
	Doi = {10.1038/nmeth.2656},
	Institution = {iMinds Future Health Department, Leuven, Belgium. [3].},
	Journal = {Nat Methods},
	Keywords = {Databases, Genetic; Genetic Predisposition to Disease; Genome, Human; Humans; Mutation; Phenotype; Polymorphism, Single Nucleotide},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Nov},
	Number = {11},
	Owner = {peter},
	Pages = {1083--1084},
	Pii = {nmeth.2656},
	Pmid = {24076761},
	Timestamp = {2015.08.09},
	Title = {{eXtasy}: variant prioritization by genomic data fusion.},
	Url = {http://dx.doi.org/10.1038/nmeth.2656},
	Volume = {10},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nmeth.2656}}

@article{Singleton2014,
	Abstract = {Phevor integrates phenotype, gene function, and disease information
	with personal genomic data for improved power to identify disease-causing
	alleles. Phevor works by combining knowledge resident in multiple
	biomedical ontologies with the outputs of variant-prioritization
	tools. It does so by using an algorithm that propagates information
	across and between ontologies. This process enables Phevor to accurately
	reprioritize potentially damaging alleles identified by variant-prioritization
	tools in light of gene function, disease, and phenotype knowledge.
	Phevor is especially useful for single-exome and family-trio-based
	diagnostic analyses, the most commonly occurring clinical scenarios
	and ones for which existing personal genome diagnostic tools are
	most inaccurate and underpowered. Here, we present a series of benchmark
	analyses illustrating Phevor's performance characteristics. Also
	presented are three recent Utah Genome Project case studies in which
	Phevor was used to identify disease-causing alleles. Collectively,
	these results show that Phevor improves diagnostic accuracy not only
	for individuals presenting with established disease phenotypes but
	also for those with previously undescribed and atypical disease presentations.
	Importantly, Phevor is not limited to known diseases or known disease-causing
	alleles. As we demonstrate, Phevor can also use latent information
	in ontologies to discover genes and disease-causing alleles not previously
	associated with disease.},
	Author = {Singleton, Marc V. and Guthery, Stephen L. and Voelkerding, Karl V. and Chen, Karin and Kennedy, Brett and Margraf, Rebecca L. and Durtschi, Jacob and Eilbeck, Karen and Reese, Martin G. and Jorde, Lynn B. and Huff, Chad D. and Yandell, Mark},
	Doi = {10.1016/j.ajhg.2014.03.010},
	Institution = {Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT 84112, USA; Utah Science, Technology, and Research Center for Genetic Discovery, University of Utah, Salt Lake City, UT 84112, USA. Electronic address: myandell@genetics.utah.edu.},
	Journal = {Am J Hum Genet},
	Keywords = {Alleles; Databases, Genetic; Genetic Predisposition to Disease; Humans; Mutation},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Apr},
	Number = {4},
	Owner = {peter},
	Pages = {599--610},
	Pii = {S0002-9297(14)00112-8},
	Pmid = {24702956},
	Timestamp = {2015.08.09},
	Title = {Phevor combines multiple biomedical ontologies for accurate identification of disease-causing alleles in single individuals and small nuclear families.},
	Url = {http://dx.doi.org/10.1016/j.ajhg.2014.03.010},
	Volume = {94},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.ajhg.2014.03.010}}
{Smedley2015a,
	Author = {Smedley, Damian and Jacobsen, Julius and J{\{"a}}ger, M and K{\"{o}}hler, Sebastian and Holtgrewe, Manuel and Schubach, Max and Siragusa, Enrico and Zemojtel, Tomasz and Buske, Orion and Bone, William P. and Haendel, Melissa and Robinson, Peter N.},
	Journal = {Nat Protocols},
	Owner = {peter},
	Timestamp = {2015.09.23},
	Title = {Next-Generation Diagnostics and Disease Gene Discovery with the Exomiser},
	Volume = {in press},
	Year = {2015}}

@article{Smedley2015,
	Abstract = {Whole exome sequencing has altered the way in which rare diseases
	are diagnosed and disease genes identified. Hundreds of novel disease-associated
	genes have been characterized by whole exome sequencing in the past
	five years, yet the identification of disease-causing mutations is
	often challenging because of the large number of rare variants that
	are being revealed. Gene prioritization aims to rank the most probable
	candidate genes towards the top of a list of potentially pathogenic
	variants. A promising new approach involves the computational comparison
	of the phenotypic abnormalities of the individual being investigated
	with those previously associated with human diseases or genetically
	modified model organisms. In this review, we compare and contrast
	the strengths and weaknesses of current phenotype-driven computational
	algorithms, including Phevor, Phen-Gen, eXtasy and two algorithms
	developed by our groups called PhenIX and Exomiser. Computational
	phenotype analysis can substantially improve the performance of exome
	analysis pipelines.},
	Author = {Smedley, Damian and Robinson, Peter N.},
	Doi = {10.1186/s13073-015-0199-2},
	Institution = {Institute for Medical Genetics and Human Genetics, Charit{\'e}-Universit{\"a}tsmedizin Berlin, Berlin, Germany ; Max Planck Institute for Molecular Genetics, Ihnestrasse, 14195 Berlin, Germany ; Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charit{\'e}-Universit{\"a}tsmedizin Berlin, Augustenburger Platz, 13353 Berlin, Germany ; Institute for Bioinformatics, Department of Mathematics and Computer Science, Freie Universit{\"a}t Berlin, Takustrasse, 14195 Berlin, Germany.},
	Journal = {Genome Med},
	Language = {eng},
	Medline-Pst = {epublish},
	Number = {1},
	Owner = {peter},
	Pages = {81},
	Pii = {199},
	Pmid = {26229552},
	Timestamp = {2015.08.05},
	Title = {Phenotype-driven strategies for exome prioritization of human {M}endelian disease genes.},
	Url = {http://dx.doi.org/10.1186/s13073-015-0199-2},
	Volume = {7},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/s13073-015-0199-2}}

@article{Soden2014,
	Abstract = {Neurodevelopmental disorders (NDDs) affect more than 3\% of children
	and are attributable to single-gene mutations at more than 1000 loci.
	Traditional methods yield molecular diagnoses in less than one-half
	of children with NDD. Whole-genome sequencing (WGS) and whole-exome
	sequencing (WES) can enable diagnosis of NDD, but their clinical
	and cost-effectiveness are unknown. One hundred families with 119
	children affected by NDD received diagnostic WGS and/or WES of parent-child
	trios, wherein the sequencing approach was guided by acuity of illness.
	Forty-five percent received molecular diagnoses. An accelerated sequencing
	modality, rapid WGS, yielded diagnoses in 73\% of families with acutely
	ill children (11 of 15). Forty percent of families with children
	with nonacute NDD, followed in ambulatory care clinics (34 of 85),
	received diagnoses: 33 by WES and 1 by staged WES then WGS. The cost
	of prior negative tests in the nonacute patients was $19,100 per
	family, suggesting sequencing to be cost-effective at up to $7640
	per family. A change in clinical care or impression of the pathophysiology
	was reported in 49\% of newly diagnosed families. If WES or WGS had
	been performed at symptom onset, genomic diagnoses may have been
	made 77 months earlier than occurred in this study. It is suggested
	that initial diagnostic evaluation of children with NDD should include
	trio WGS or WES, with extension of accelerated sequencing modalities
	to high-acuity patients.},
	Author = {Soden, Sarah E. and Saunders, Carol J. and Willig, Laurel K. and Farrow, Emily G. and Smith, Laurie D. and Petrikin, Josh E. and LePichon, Jean-Baptiste and Miller, Neil A. and Thiffault, Isabelle and Dinwiddie, Darrell L. and Twist, Greyson and Noll, Aaron and Heese, Bryce A. and Zellmer, Lee and Atherton, Andrea M. and Abdelmoity, Ahmed T. and Safina, Nicole and Nyp, Sarah S. and Zuccarelli, Britton and Larson, Ingrid A. and Modrcin, Ann and Herd, Suzanne and Creed, Mitchell and Ye, Zhaohui and Yuan, Xuan and Brodsky, Robert A. and Kingsmore, Stephen F.},
	Doi = {10.1126/scitranslmed.3010076},
	Institution = {Center for Pediatric Genomic Medicine, Children's Mercy-Kansas City, Kansas City, MO 64108, USA. Department of Pediatrics, Children's Mercy-Kansas City, Kansas City, MO 64108, USA. School of Medicine, University of Missouri-Kansas City, Kansas City, MO 64108, USA. Department of Pathology, Children's Mercy-Kansas City, Kansas City, MO 64108, USA.},
	Journal = {Sci Transl Med},
	Keywords = {Base Sequence; Child; Child, Preschool; DNA Mutational Analysis; Developmental Disabilities, diagnosis/genetics; Exome; Female; Genetic Predisposition to Disease; Genome; Genome, Human; Health Care Costs; Humans; Infant; Male; Molecular Diagnostic Techniques, methods; Mutation; Phenotype; Sequence Analysis, DNA, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Dec},
	Number = {265},
	Owner = {peter},
	Pages = {265ra168},
	Pii = {6/265/265ra168},
	Pmid = {25473036},
	Timestamp = {2015.08.09},
	Title = {Effectiveness of exome and genome sequencing guided by acuity of illness for diagnosis of neurodevelopmental disorders.},
	Url = {http://dx.doi.org/10.1126/scitranslmed.3010076},
	Volume = {6},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1126/scitranslmed.3010076}}

@article{Stenson2014,
	Abstract = {The Human Gene Mutation Database (HGMD{\textregistered}) is a comprehensive
	collection of germline mutations in nuclear genes that underlie,
	or are associated with, human inherited disease. By June 2013, the
	database contained over 141,000 different lesions detected in over
	5,700 different genes, with new mutation entries currently accumulating
	at a rate exceeding 10,000 per annum. HGMD was originally established
	in 1996 for the scientific study of mutational mechanisms in human
	genes. However, it has since acquired a much broader utility as a
	central unified disease-oriented mutation repository utilized by
	human molecular geneticists, genome scientists, molecular biologists,
	clinicians and genetic counsellors as well as by those specializing
	in biopharmaceuticals, bioinformatics and personalized genomics.
	The public version of HGMD (http://www.hgmd.org) is freely available
	to registered users from academic institutions/non-profit organizations
	whilst the subscription version (HGMD Professional) is available
	to academic, clinical and commercial users under license via BIOBASE
	GmbH.},
	Author = {Stenson, Peter D. and Mort, Matthew and Ball, Edward V. and Shaw, Katy and Phillips, Andrew and Cooper, David N.},
	Doi = {10.1007/s00439-013-1358-4},
	Journal = {Hum Genet},
	Keywords = {Cell Nucleus, genetics; Computational Biology; DNA Copy Number Variations; Databases, Genetic; Genetic Predisposition to Disease; Genetic Testing; Genome, Human; Genomics; Germ-Line Mutation; Humans; Individualized Medicine; Polymorphism, Genetic},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {1},
	Owner = {peter},
	Pages = {1--9},
	Pmid = {24077912},
	Timestamp = {2015.08.09},
	Title = {The {Human Gene Mutation Database}: building a comprehensive mutation repository for clinical and molecular genetics, diagnostic testing and personalized genomic medicine.},
	Url = {http://dx.doi.org/10.1007/s00439-013-1358-4},
	Volume = {133},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1007/s00439-013-1358-4}}

@article{Taylor2015,
	Abstract = {To assess factors influencing the success of whole-genome sequencing
	for mainstream clinical diagnosis, we sequenced 217 individuals from
	156 independent cases or families across a broad spectrum of disorders
	in whom previous screening had identified no pathogenic variants.
	We quantified the number of candidate variants identified using different
	strategies for variant calling, filtering, annotation and prioritization.
	We found that jointly calling variants across samples, filtering
	against both local and external databases, deploying multiple annotation
	tools and using familial transmission above biological plausibility
	contributed to accuracy. Overall, we identified disease-causing variants
	in 21\% of cases, with the proportion increasing to 34\% (23/68)
	for mendelian disorders and 57\% (8/14) in family trios. We also
	discovered 32 potentially clinically actionable variants in 18 genes
	unrelated to the referral disorder, although only 4 were ultimately
	considered reportable. Our results demonstrate the value of genome
	sequencing for routine clinical diagnosis but also highlight many
	outstanding challenges.},
	Author = {Taylor, Jenny C. and Martin, Hilary C. and Lise, Stefano and Broxholme, John and Cazier, Jean-Baptiste and Rimmer, Andy and Kanapin, Alexander and Lunter, Gerton and Fiddy, Simon and Allan, Chris and Aricescu, A Radu and Attar, Moustafa and Babbs, Christian and Becq, Jennifer and Beeson, David and Bento, Celeste and Bignell, Patricia and Blair, Edward and Buckle, Veronica J. and Bull, Katherine and Cais, Ondrej and Cario, Holger and Chapel, Helen and Copley, Richard R. and Cornall, Richard and Craft, Jude and Dahan, Karin and Davenport, Emma E. and Dendrou, Calliope and Devuyst, Olivier and Fenwick, Aim{\'{e}}e L. and Flint, Jonathan and Fugger, Lars and Gilbert, Rodney D. and Goriely, Anne and Green, Angie and Greger, Ingo H. and Grocock, Russell and Gruszczyk, Anja V. and Hastings, Robert and Hatton, Edouard and Higgs, Doug and Hill, Adrian and Holmes, Chris and Howard, Malcolm and Hughes, Linda and Humburg, Peter and Johnson, David and Karpe, Fredrik and Kingsbury, Zoya and Kini, Usha and Knight, Julian C. and Krohn, Jonathan and Lamble, Sarah and Langman, Craig and Lonie, Lorne and Luck, Joshua and McCarthy, Davis and McGowan, Simon J. and McMullin, Mary Frances and Miller, Kerry A. and Murray, Lisa and N{\'{e}}meth, Andrea H. and Nesbit, M Andrew and Nutt, David and Ormondroyd, Elizabeth and Oturai, Annette Bang and Pagnamenta, Alistair and Patel, Smita Y. and Percy, Melanie and Petousi, Nayia and Piazza, Paolo and Piret, Sian E. and Polanco-Echeverry, Guadalupe and Popitsch, Niko and Powrie, Fiona and Pugh, Chris and Quek, Lynn and Robbins, Peter A. and Robson, Kathryn and Russo, Alexandra and Sahgal, Natasha and {van Schouwenburg}, Pauline A. and Schuh, Anna and Silverman, Earl and Simmons, Alison and S{\o}rensen, Per Soelberg and Sweeney, Elizabeth and Taylor, John and Thakker, Rajesh V. and Tomlinson, Ian and Trebes, Amy and Twigg, Stephen R F. and Uhlig, Holm H. and Vyas, Paresh and Vyse, Tim and Wall, Steven A. and Watkins, Hugh and Whyte, Michael P. and Witty, Lorna and Wright, Ben and Yau, Chris and Buck, David and Humphray, Sean and Ratcliffe, Peter J. and Bell, John I. and Wilkie, Andrew O M. and Bentley, David and Donnelly, Peter and McVean, Gilean},
	Doi = {10.1038/ng.3304},
	Institution = {Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.},
	Journal = {Nat Genet},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jul},
	Number = {7},
	Owner = {peter},
	Pages = {717--726},
	Pii = {ng.3304},
	Pmid = {25985138},
	Timestamp = {2015.08.05},
	Title = {Factors influencing success of clinical genome sequencing across a broad spectrum of disorders.},
	Url = {http://dx.doi.org/10.1038/ng.3304},
	Volume = {47},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/ng.3304}}

@article{VanderMeer2011,
	Abstract = {The underlying mutations that cause human limb malformations are often
	difficult to determine, particularly for limb malformations that
	occur as isolated traits. Evidence from a variety of studies shows
	that cis-regulatory mutations, specifically in enhancers, can lead
	to some of these isolated limb malformations. Here, we provide a
	review of human limb malformations that have been shown to be caused
	by enhancer mutations and propose that cis-regulatory mutations will
	continue to be identified as the cause of additional human malformations
	as our understanding of regulatory sequences improves.},
	Author = {VanderMeer, Julia E. and Ahituv, Nadav},
	Doi = {10.1002/dvdy.22535},
	Institution = {Department of Bioengineering and Therapeutic Sciences, and Institute for Human Genetics, University of California San Francisco, San Francisco, California, USA.},
	Journal = {Dev Dyn},
	Keywords = {Gene Expression Regulation, Developmental, genetics/physiology; Humans; Limb Deformities, Congenital, genetics; Mutation; Regulatory Sequences, Nucleic Acid, genetics},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {May},
	Number = {5},
	Owner = {peter},
	Pages = {920--930},
	Pmid = {21509892},
	Timestamp = {2015.08.06},
	Title = {cis-regulatory mutations are a genetic cause of human limb malformations.},
	Url = {http://dx.doi.org/10.1002/dvdy.22535},
	Volume = {240},
	Year = {2011},
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/dvdy.22535}}

@article{Veltman2015,
	Abstract = {Next-generation sequencing is revolutionizing medical genetics and
	in the near future will pervade all medical fields. To maximize the
	potential clinical utility of this approach, global data sharing
	and phenotyping are needed, and the role of the geneticist in the
	interpretation of variation is vital.},
	Author = {Veltman, Joris A. and Lupski, James R.},
	Doi = {10.1186/s13073-015-0200-0},
	Institution = {Department of Molecular and Human Genetics, Department of Pediatrics, and Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza Room 604B, Houston, TX 77030 USA ; Texas Children's Hospital, Houston, TX 77030 USA.},
	Journal = {Genome Med},
	Language = {eng},
	Medline-Pst = {epublish},
	Number = {1},
	Owner = {peter},
	Pages = {78},
	Pii = {200},
	Pmid = {26221187},
	Timestamp = {2015.08.05},
	Title = {From genes to genomes in the clinic.},
	Url = {http://dx.doi.org/10.1186/s13073-015-0200-0},
	Volume = {7},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/s13073-015-0200-0}}

@article{Wapner2012,
	Abstract = {BACKGROUND: Chromosomal microarray analysis has emerged as a primary
	diagnostic tool for the evaluation of developmental delay and structural
	malformations in children. We aimed to evaluate the accuracy, efficacy,
	and incremental yield of chromosomal microarray analysis as compared
	with karyotyping for routine prenatal diagnosis.
	
	METHODS: Samples from women undergoing prenatal diagnosis at 29 centers
	were sent to a central karyotyping laboratory. Each sample was split
	in two; standard karyotyping was performed on one portion and the
	other was sent to one of four laboratories for chromosomal microarray.
	
	RESULTS: We enrolled a total of 4406 women. Indications for prenatal
	diagnosis were advanced maternal age (46.6\%), abnormal result on
	Down's syndrome screening (18.8\%), structural anomalies on ultrasonography
	(25.2\%), and other indications (9.4\%). In 4340 (98.8\%) of the
	fetal samples, microarray analysis was successful; 87.9\% of samples
	could be used without tissue culture. Microarray analysis of the
	4282 nonmosaic samples identified all the aneuploidies and unbalanced
	rearrangements identified on karyotyping but did not identify balanced
	translocations and fetal triploidy. In samples with a normal karyotype,
	microarray analysis revealed clinically relevant deletions or duplications
	in 6.0\% with a structural anomaly and in 1.7\% of those whose indications
	were advanced maternal age or positive screening results.
	
	CONCLUSIONS: In the context of prenatal diagnostic testing, chromosomal
	microarray analysis identified additional, clinically significant
	cytogenetic information as compared with karyotyping and was equally
	efficacious in identifying aneuploidies and unbalanced rearrangements
	but did not identify balanced translocations and triploidies. (Funded
	by the Eunice Kennedy Shriver National Institute of Child Health
	and Human Development and others; ClinicalTrials.gov number, NCT01279733.).},
	Author = {Wapner, Ronald J and Martin, Christa Lese and Levy, Brynn and Ballif, Blake C and Eng, Christine M and Zachary, Julia M and Savage, Melissa and Platt, Lawrence D and Saltzman, Daniel and Grobman, William A and Klugman, Susan and Scholl, Thomas and Simpson, Joe Leigh and McCall, Kimberly and Aggarwal, Vimla S and Bunke, Brian and Nahum, Odelia and Patel, Ankita and Lamb, Allen N and Thom, Elizabeth A and Beaudet, Arthur L and Ledbetter, David H and Shaffer, Lisa G and Jackson, Laird},
	Doi = {10.1056/NEJMoa1203382},
	Issn = {1533-4406},
	Journal = {The New England journal of medicine},
	Keywords = {Adult,Chromosome Aberrations,Chromosome Disorders,Chromosome Disorders: diagnosis,Chromosomes, Human,Chromosomes, Human: genetics,Down Syndrome,Down Syndrome: diagnosis,Female,Fetal Diseases,Fetal Diseases: diagnosis,Genetic Testing,Genetic Testing: methods,Humans,Karyotype,Karyotyping,Maternal Age,Oligonucleotide Array Sequence Analysis,Pregnancy,Prenatal Diagnosis,Prenatal Diagnosis: methods,Ultrasonography, Prenatal},
	Month = dec,
	Number = {23},
	Pages = {2175--84},
	Pmid = {23215555},
	Title = {{Chromosomal microarray versus karyotyping for prenatal diagnosis.}},
	Url = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3549418\&tool=pmcentrez\&rendertype=abstract},
	Volume = {367},
	Year = {2012},
	Bdsk-Url-1 = {http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3549418%5C&tool=pmcentrez%5C&rendertype=abstract},
	Bdsk-Url-2 = {http://dx.doi.org/10.1056/NEJMoa1203382}}

@article{Ward2012,
	Abstract = {Association studies provide genome-wide information about the genetic
	basis of complex disease, but medical research has focused primarily
	on protein-coding variants, owing to the difficulty of interpreting
	noncoding mutations. This picture has changed with advances in the
	systematic annotation of functional noncoding elements. Evolutionary
	conservation, functional genomics, chromatin state, sequence motifs
	and molecular quantitative trait loci all provide complementary information
	about the function of noncoding sequences. These functional maps
	can help with prioritizing variants on risk haplotypes, filtering
	mutations encountered in the clinic and performing systems-level
	analyses to reveal processes underlying disease associations. Advances
	in predictive modeling can enable data-set integration to reveal
	pathways shared across loci and alleles, and richer regulatory models
	can guide the search for epistatic interactions. Lastly, new massively
	parallel reporter experiments can systematically validate regulatory
	predictions. Ultimately, advances in regulatory and systems genomics
	can help unleash the value of whole-genome sequencing for personalized
	genomic risk assessment, diagnosis and treatment.},
	Author = {Ward, Lucas D. and Kellis, Manolis},
	Doi = {10.1038/nbt.2422},
	Institution = {Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. lukeward@mit.edu},
	Journal = {Nat Biotechnol},
	Keywords = {Animals; Chromosome Mapping, methods; Genetic Predisposition to Disease, genetics; Genetic Testing, methods; Genetic Variation, genetics; Humans; Quantitative Trait Loci, genetics; RNA, Untranslated, genetics; Sequence Analysis, DNA, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Nov},
	Number = {11},
	Owner = {peter},
	Pages = {1095--1106},
	Pii = {nbt.2422},
	Pmid = {23138309},
	Timestamp = {2015.07.18},
	Title = {Interpreting noncoding genetic variation in complex traits and human disease.},
	Url = {http://dx.doi.org/10.1038/nbt.2422},
	Volume = {30},
	Year = {2012},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nbt.2422}}

@article{Welter2014,
	Abstract = {The National Human Genome Research Institute (NHGRI) Catalog of Published
	Genome-Wide Association Studies (GWAS) Catalog provides a publicly
	available manually curated collection of published GWAS assaying
	at least 100,000 single-nucleotide polymorphisms (SNPs) and all SNP-trait
	associations with P <1 × 10(-5). The Catalog includes 1751 curated
	publications of 11 912 SNPs. In addition to the SNP-trait association
	data, the Catalog also publishes a quarterly diagram of all SNP-trait
	associations mapped to the SNPs' chromosomal locations. The Catalog
	can be accessed via a tabular web interface, via a dynamic visualization
	on the human karyotype, as a downloadable tab-delimited file and
	as an OWL knowledge base. This article presents a number of recent
	improvements to the Catalog, including novel ways for users to interact
	with the Catalog and changes to the curation infrastructure.},
	Author = {Welter, Danielle and MacArthur, Jacqueline and Morales, Joannella and Burdett, Tony and Hall, Peggy and Junkins, Heather and Klemm, Alan and Flicek, Paul and Manolio, Teri and Hindorff, Lucia and Parkinson, Helen},
	Doi = {10.1093/nar/gkt1229},
	Institution = {European Bioinformatics Institute (EMBL-EBI), European Molecular Biology Laboratory, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK, Division of Genomic Medicine, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA and Division of Policy, Communication and Education, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.},
	Journal = {Nucleic Acids Res},
	Keywords = {Databases, Nucleic Acid; Gene Ontology; Genome, Human; Genome-Wide Association Study; Humans; Internet; Karyotype; Polymorphism, Single Nucleotide},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Jan},
	Number = {Database issue},
	Owner = {peter},
	Pages = {D1001--D1006},
	Pii = {gkt1229},
	Pmid = {24316577},
	Timestamp = {2015.08.09},
	Title = {The {NHGRI GWAS Catalog}, a curated resource of {SNP}-trait associations.},
	Url = {http://dx.doi.org/10.1093/nar/gkt1229},
	Volume = {42},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1093/nar/gkt1229}}

@article{Wethmar2010,
	Abstract = {Conserved upstream open reading frames (uORFs) are found within many
	eukaryotic transcripts and are known to regulate protein translation.
	Evidence from genetic and bioinformatic studies implicates disturbed
	uORF-mediated translational control in the etiology of human diseases.
	A genetic mouse model has recently provided proof-of-principle support
	for the physiological relevance of uORF-mediated translational control
	in mammals. The targeted disruption of the uORF initiation codon
	within the transcription factor CCAAT/enhancer binding protein $\beta$
	(C/EBP$\beta$) gene resulted in deregulated C/EBP$\beta$ protein
	isoform expression, associated with defective liver regeneration
	and impaired osteoclast differentiation. The high prevalence of uORFs
	in the human transcriptome suggests that intensified search for mutations
	within 5' RNA leader regions may reveal a multitude of alterations
	affecting uORFs, causing pathogenic deregulation of protein expression.},
	Author = {Wethmar, Klaus and Smink, Jeske J. and Leutz, Achim},
	Doi = {10.1002/bies.201000037},
	Institution = {Max Delbrueck Center for Molecular Medicine, Berlin, Germany.},
	Journal = {Bioessays},
	Keywords = {5' Untranslated Regions; Animals; CCAAT-Enhancer-Binding Protein-beta, metabolism; Codon, Initiator, metabolism; Gene Expression Regulation; Humans; Mice; Mutation; Open Reading Frames; Protein Biosynthesis; RNA, Messenger, metabolism; Transcription Factors},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Oct},
	Number = {10},
	Owner = {peter},
	Pages = {885--893},
	Pmid = {20726009},
	Timestamp = {2015.08.05},
	Title = {Upstream open reading frames: molecular switches in (patho)physiology.},
	Url = {http://dx.doi.org/10.1002/bies.201000037},
	Volume = {32},
	Year = {2010},
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/bies.201000037}}

@article{Yang2013,
	Abstract = {Whole-exome sequencing is a diagnostic approach for the identification
	of molecular defects in patients with suspected genetic disorders.We
	developed technical, bioinformatic, interpretive, and validation
	pipelines for whole-exome sequencing in a certified clinical laboratory
	to identify sequence variants underlying disease phenotypes in patients.We
	present data on the first 250 probands for whom referring physicians
	ordered whole-exome sequencing. Patients presented with a range of
	phenotypes suggesting potential genetic causes. Approximately 80\%
	were children with neurologic phenotypes. Insurance coverage was
	similar to that for established genetic tests. We identified 86 mutated
	alleles that were highly likely to be causative in 62 of the 250
	patients, achieving a 25\% molecular diagnostic rate (95\% confidence
	interval, 20 to 31). Among the 62 patients, 33 had autosomal dominant
	disease, 16 had autosomal recessive disease, and 9 had X-linked disease.
	A total of 4 probands received two nonoverlapping molecular diagnoses,
	which potentially challenged the clinical diagnosis that had been
	made on the basis of history and physical examination. A total of
	83\% of the autosomal dominant mutant alleles and 40\% of the X-linked
	mutant alleles occurred de novo. Recurrent clinical phenotypes occurred
	in patients with mutations that were highly likely to be causative
	in the same genes and in different genes responsible for genetically
	heterogeneous disorders.Whole-exome sequencing identified the underlying
	genetic defect in 25\% of consecutive patients referred for evaluation
	of a possible genetic condition. (Funded by the National Human Genome
	Research Institute.).},
	Author = {Yang, Yaping and Muzny, Donna M. and Reid, Jeffrey G. and Bainbridge, Matthew N. and Willis, Alecia and Ward, Patricia A. and Braxton, Alicia and Beuten, Joke and Xia, Fan and Niu, Zhiyv and Hardison, Matthew and Person, Richard and Bekheirnia, Mir Reza and Leduc, Magalie S. and Kirby, Amelia and Pham, Peter and Scull, Jennifer and Wang, Min and Ding, Yan and Plon, Sharon E. and Lupski, James R. and Beaudet, Arthur L. and Gibbs, Richard A. and Eng, Christine M.},
	Doi = {10.1056/NEJMoa1306555},
	Institution = {Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.},
	Journal = {N Engl J Med},
	Keywords = {Adolescent; Child; Child, Preschool; Exome; Genes, Dominant; Genes, Recessive; Genes, X-Linked; Genetic Diseases, Inborn, diagnosis/genetics; Genetic Testing, methods; Humans; Mutation; Phenotype; Sequence Analysis, DNA, methods; Young Adult},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Oct},
	Number = {16},
	Owner = {peter},
	Pages = {1502--1511},
	Pmid = {24088041},
	Timestamp = {2015.08.09},
	Title = {Clinical whole-exome sequencing for the diagnosis of mendelian disorders.},
	Url = {http://dx.doi.org/10.1056/NEJMoa1306555},
	Volume = {369},
	Year = {2013},
	Bdsk-Url-1 = {http://dx.doi.org/10.1056/NEJMoa1306555}}

@article{Yang2014,
	Abstract = {Clinical whole-exome sequencing is increasingly used for diagnostic
	evaluation of patients with suspected genetic disorders.To perform
	clinical whole-exome sequencing and report (1) the rate of molecular
	diagnosis among phenotypic groups, (2) the spectrum of genetic alterations
	contributing to disease, and (3) the prevalence of medically actionable
	incidental findings such as FBN1 mutations causing Marfan syndrome.Observational
	study of 2000 consecutive patients with clinical whole-exome sequencing
	analyzed between June 2012 and August 2014. Whole-exome sequencing
	tests were performed at a clinical genetics laboratory in the United
	States. Results were reported by clinical molecular geneticists certified
	by the American Board of Medical Genetics and Genomics. Tests were
	ordered by the patient's physician. The patients were primarily pediatric
	(1756 [88\%]; mean age, 6 years; 888 females [44\%], 1101 males [55\%],
	and 11 fetuses [1\% gender unknown]), demonstrating diverse clinical
	manifestations most often including nervous system dysfunction such
	as developmental delay.Whole-exome sequencing diagnosis rate overall
	and by phenotypic category, mode of inheritance, spectrum of genetic
	events, and reporting of incidental findings.A molecular diagnosis
	was reported for 504 patients (25.2\%) with 58\% of the diagnostic
	mutations not previously reported. Molecular diagnosis rates for
	each phenotypic category were 143/526 (27.2\%; 95\% CI, 23.5\%-31.2\%)
	for the neurological group, 282/1147 (24.6\%; 95\% CI, 22.1\%-27.2\%)
	for the neurological plus other organ systems group, 30/83 (36.1\%;
	95\% CI, 26.1\%-47.5\%) for the specific neurological group, and
	49/244 (20.1\%; 95\% CI, 15.6\%-25.8\%) for the nonneurological group.
	The Mendelian disease patterns of the 527 molecular diagnoses included
	280 (53.1\%) autosomal dominant, 181 (34.3\%) autosomal recessive
	(including 5 with uniparental disomy), 65 (12.3\%) X-linked, and
	1 (0.2\%) mitochondrial. Of 504 patients with a molecular diagnosis,
	23 (4.6\%) had blended phenotypes resulting from 2 single gene defects.
	About 30\% of the positive cases harbored mutations in disease genes
	reported since 2011. There were 95 medically actionable incidental
	findings in genes unrelated to the phenotype but with immediate implications
	for management in 92 patients (4.6\%), including 59 patients (3\%)
	with mutations in genes recommended for reporting by the American
	College of Medical Genetics and Genomics.Whole-exome sequencing provided
	a potential molecular diagnosis for 25\% of a large cohort of patients
	referred for evaluation of suspected genetic conditions, including
	detection of rare genetic events and new mutations contributing to
	disease. The yield of whole-exome sequencing may offer advantages
	over traditional molecular diagnostic approaches in certain patients.},
	Author = {Yang, Yaping and Muzny, Donna M. and Xia, Fan and Niu, Zhiyv and Person, Richard and Ding, Yan and Ward, Patricia and Braxton, Alicia and Wang, Min and Buhay, Christian and Veeraraghavan, Narayanan and Hawes, Alicia and Chiang, Theodore and Leduc, Magalie and Beuten, Joke and Zhang, Jing and He, Weimin and Scull, Jennifer and Willis, Alecia and Landsverk, Megan and Craigen, William J. and Bekheirnia, Mir Reza and Stray-Pedersen, Asbjorg and Liu, Pengfei and Wen, Shu and Alcaraz, Wendy and Cui, Hong and Walkiewicz, Magdalena and Reid, Jeffrey and Bainbridge, Matthew and Patel, Ankita and Boerwinkle, Eric and Beaudet, Arthur L. and Lupski, James R. and Plon, Sharon E. and Gibbs, Richard A. and Eng, Christine M.},
	Doi = {10.1001/jama.2014.14601},
	Institution = {Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas.},
	Journal = {JAMA},
	Keywords = {Adolescent; Adult; Child; Child, Preschool; Exome; Female; Fetus; Genetic Diseases, Inborn, diagnosis; Genetic Testing; Genomics; Humans; Incidental Findings; Infant; Infant, Newborn; Male; Molecular Diagnostic Techniques; Mutation; Phenotype; Referral and Consultation; Sequence Analysis, DNA, methods},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Nov},
	Number = {18},
	Owner = {peter},
	Pages = {1870--1879},
	Pii = {1918774},
	Pmid = {25326635},
	Timestamp = {2015.08.09},
	Title = {Molecular findings among patients referred for clinical whole-exome sequencing.},
	Url = {http://dx.doi.org/10.1001/jama.2014.14601},
	Volume = {312},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1001/jama.2014.14601}}

@article{Yeo2004,
	Abstract = {We propose a framework for modeling sequence motifs based on the maximum
	entropy principle (MEP). We recommend approximating short sequence
	motif distributions with the maximum entropy distribution (MED) consistent
	with low-order marginal constraints estimated from available data,
	which may include dependencies between nonadjacent as well as adjacent
	positions. Many maximum entropy models (MEMs) are specified by simply
	changing the set of constraints. Such models can be utilized to discriminate
	between signals and decoys. Classification performance using different
	MEMs gives insight into the relative importance of dependencies between
	different positions. We apply our framework to large datasets of
	RNA splicing signals. Our best models out-perform previous probabilistic
	models in the discrimination of human 5' (donor) and 3' (acceptor)
	splice sites from decoys. Finally, we discuss mechanistically motivated
	ways of comparing models.},
	Author = {Yeo, Gene and Burge, Christopher B.},
	Doi = {10.1089/1066527041410418},
	Institution = {Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue Building 68-223, Cambridge, MA 02319, USA.},
	Journal = {J Comput Biol},
	Keywords = {Base Sequence; Computational Biology; Consensus Sequence; Introns; Markov Chains; Models, Genetic; Phylogeny; RNA Splice Sites; ROC Curve},
	Language = {eng},
	Medline-Pst = {ppublish},
	Number = {2-3},
	Owner = {peter},
	Pages = {377--394},
	Pmid = {15285897},
	Timestamp = {2015.09.13},
	Title = {Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals.},
	Url = {http://dx.doi.org/10.1089/1066527041410418},
	Volume = {11},
	Year = {2004},
	Bdsk-Url-1 = {http://dx.doi.org/10.1089/1066527041410418}}

@article{Zemojtel2014,
	Abstract = {Less than half of patients with suspected genetic disease receive
	a molecular diagnosis. We have therefore integrated next-generation
	sequencing (NGS), bioinformatics, and clinical data into an effective
	diagnostic workflow. We used variants in the 2741 established Mendelian
	disease genes [the disease-associated genome (DAG)] to develop a
	targeted enrichment DAG panel (7.1 Mb), which achieves a coverage
	of 20-fold or better for 98\% of bases. Furthermore, we established
	a computational method [Phenotypic Interpretation of eXomes (PhenIX)]
	that evaluated and ranked variants based on pathogenicity and semantic
	similarity of patients' phenotype described by Human Phenotype Ontology
	(HPO) terms to those of 3991 Mendelian diseases. In computer simulations,
	ranking genes based on the variant score put the true gene in first
	place less than 5\% of the time; PhenIX placed the correct gene in
	first place more than 86\% of the time. In a retrospective test of
	PhenIX on 52 patients with previously identified mutations and known
	diagnoses, the correct gene achieved a mean rank of 2.1. In a prospective
	study on 40 individuals without a diagnosis, PhenIX analysis enabled
	a diagnosis in 11 cases (28\%, at a mean rank of 2.4). Thus, the
	NGS of the DAG followed by phenotype-driven bioinformatic analysis
	allows quick and effective differential diagnostics in medical genetics.},
	Author = {Zemojtel, Tomasz and K{\"{o}}hler, Sebastian and Mackenroth, Luisa and J{\"{a}}ger, Marten and Hecht, Jochen and Krawitz, Peter and Graul-Neumann, Luitgard and Doelken, Sandra and Ehmke, Nadja and Spielmann, Malte and Oien, Nancy Christine and Schweiger, Michal R. and Kr{\"{u}}ger, Ulrike and Frommer, G{\"{o}}tz and Fischer, Bj{\"{o}}rn and Kornak, Uwe and Fl{\"{o}}ttmann, Ricarda and Ardeshirdavani, Amin and Moreau, Yves and Lewis, Suzanna E. and Haendel, Melissa and Smedley, Damian and Horn, Denise and Mundlos, Stefan and Robinson, Peter N.},
	Doi = {10.1126/scitranslmed.3009262},
	Institution = {Institute for Medical Genetics and Human Genetics, Charit{\'e} Universit{\"a}tsmedizin Berlin, Augustenburger Platz 1, 13353 Berlin, Germany. Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, 14195 Berlin, Germany. Berlin-Brandenburg Center for Regenerative Therapies, Charit{\'e} Universit{\"a}tsmedizin Berlin, 13353 Berlin, Germany. Institute for Bioinformatics, Department of Mathematics and Computer Science, Freie Universit{\"a}t Berlin, Takustr. 9, 14195 Berlin, Germany. peter.robinson@charite.de.},
	Journal = {Sci Transl Med},
	Keywords = {Computational Biology, methods; Exome, genetics; Genetic Diseases, Inborn, diagnosis; Genome, Human, genetics; Humans; Mutation; Phenotype; Prospective Studies; Reproducibility of Results; Retrospective Studies},
	Language = {eng},
	Medline-Pst = {ppublish},
	Month = {Sep},
	Number = {252},
	Owner = {peter},
	Pages = {252ra123},
	Pii = {6/252/252ra123},
	Pmid = {25186178},
	Timestamp = {2015.08.05},
	Title = {Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome.},
	Url = {http://dx.doi.org/10.1126/scitranslmed.3009262},
	Volume = {6},
	Year = {2014},
	Bdsk-Url-1 = {http://dx.doi.org/10.1126/scitranslmed.3009262}}

@article{Zerbino2015,
	Abstract = {Most genomic variants associated with phenotypic traits or disease
	do not fall within gene coding regions, but in regulatory regions,
	rendering their interpretation difficult. We collected public data
	on epigenetic marks and transcription factor binding in human cell
	types and used it to construct an intuitive summary of regulatory
	regions in the human genome. We verified it against independent assays
	for sensitivity. The Ensembl Regulatory Build will be progressively
	enriched when more data is made available. It is freely available
	on the Ensembl browser, from the Ensembl Regulation MySQL database
	server and in a dedicated track hub.},
	Author = {Zerbino, Daniel R. and Wilder, Steven P. and Johnson, Nathan and Juettemann, Thomas and Flicek, Paul R.},
	Doi = {10.1186/s13059-015-0621-5},
	Institution = {European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. flicek@ebi.ac.uk.},
	Journal = {Genome Biol},
	Language = {eng},
	Medline-Pst = {epublish},
	Owner = {peter},
	Pages = {56},
	Pii = {10.1186/s13059-015-0621-5},
	Pmid = {25887522},
	Timestamp = {2015.10.01},
	Title = {The ensembl regulatory build.},
	Url = {http://dx.doi.org/10.1186/s13059-015-0621-5},
	Volume = {16},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1186/s13059-015-0621-5}}

@article{Zhou2015,
	Abstract = {Identifying functional effects of noncoding variants is a major challenge
	in human genetics. To predict the noncoding-variant effects de novo
	from sequence, we developed a deep learning-based algorithmic framework,
	DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory
	sequence code from large-scale chromatin-profiling data, enabling
	prediction of chromatin effects of sequence alterations with single-nucleotide
	sensitivity. We further used this capability to improve prioritization
	of functional variants including expression quantitative trait loci
	(eQTLs) and disease-associated variants.},
	Author = {Zhou, Jian and Troyanskaya, Olga G},
	Doi = {10.1038/nmeth.3547},
	Issn = {1548-7105},
	Journal = {Nature methods},
	Month = aug,
	Number = {10},
	Pages = {931--934},
	Pmid = {26301843},
	Publisher = {Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved.},
	Shorttitle = {Nat Meth},
	Title = {{Predicting effects of noncoding variants with deep learning-based sequence model.}},
	Url = {http://dx.doi.org/10.1038/nmeth.3547},
	Volume = {12},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/nmeth.3547}}

@article{Zhu2015,
	Abstract = {Purpose:Despite the recognized clinical value of exome-based diagnostics,
	methods for comprehensive genomic interpretation remain immature.
	Diagnoses are based on known or presumed pathogenic variants in genes
	already associated with a similar phenotype. Here, we extend this
	paradigm by evaluating novel bioinformatics approaches to aid identification
	of new gene-disease associations.Methods:We analyzed 119 trios to
	identify both diagnostic genotypes in known genes and candidate genotypes
	in novel genes. We considered qualifying genotypes based on their
	population frequency and in silico predicted effects we also characterized
	the patterns of genotypes enriched among this collection of patients.Results:We
	obtained a genetic diagnosis for 29 (24\%) of our patients. We showed
	that patients carried an excess of damaging de novo mutations in
	intolerant genes, particularly those shown to be essential in mice
	(P = 3.4?x 10(-8)). This enrichment is only partially explained by
	mutations found in known disease-causing genes.Conclusion:This work
	indicates that the application of appropriate bioinformatics analyses
	to clinical sequence data can also help implicate novel disease genes
	and suggest expanded phenotypes for known disease genes. These analyses
	further suggest that some cases resolved by whole-exome sequencing
	will have direct therapeutic implications.Genet Med advance online
	publication 15 January 2015Genetics in Medicine (2015); doi:10.1038/gim.2014.191.},
	Author = {Zhu, Xiaolin and Petrovski, Slav\'{e} and Xie, Pingxing and Ruzzo, Elizabeth K. and Lu, Yi-Fan and McSweeney, K Melodi and Ben-Zeev, Bruria and Nissenkorn, Andreea and Anikster, Yair and Oz-Levi, Danit and Dhindsa, Ryan S. and Hitomi, Yuki and Schoch, Kelly and Spillmann, Rebecca C. and Heimer, Gali and Marek-Yagel, Dina and Tzadok, Michal and Han, Yujun and Worley, Gordon and Goldstein, Jennifer and Jiang, Yong-Hui and Lancet, Doron and Pras, Elon and Shashi, Vandana and McHale, Duncan and Need, Anna C. and Goldstein, David B.},
	Doi = {10.1038/gim.2014.191},
	Institution = {Center for Human Genome Variation, Duke University School of Medicine, Durham, North Carolina, USA.},
	Journal = {Genet Med},
	Language = {eng},
	Medline-Pst = {aheadofprint},
	Month = {Jan},
	Owner = {peter},
	Pii = {gim2014191},
	Pmid = {25590979},
	Timestamp = {2015.09.28},
	Title = {Whole-exome sequencing in undiagnosed genetic diseases: interpreting 119 trios.},
	Url = {http://dx.doi.org/10.1038/gim.2014.191},
	Year = {2015},
	Bdsk-Url-1 = {http://dx.doi.org/10.1038/gim.2014.191}}

@unpublished{IchLearningfromImbalancedData,
	Date-Added = {2015-09-22 17:29:34 +0000},
	Date-Modified = {2015-09-22 17:29:40 +0000}}
	
	
@article{Lappalainen13b,
	Author = "Lappalainen and others",
	Journal = {Nature},
	Pages = {506--511},
	Title = {Transcriptome and genome sequencing uncover functional variation in humans},
	Volume = {501},
	Year = {2013}}	
	
@article{Forbes2015,
author = {Forbes, Simon A. and Beare, David and Gunasekaran, Prasad and Leung, Kenric and Bindal, Nidhi and Boutselakis, Harry and Ding, Minjie and Bamford, Sally and Cole, Charlotte and Ward, Sari and Kok, Chai Yin and Jia, Mingming and De, Tisham and Teague, Jon W. and Stratton, Michael R. and McDermott, Ultan and Campbell, Peter J.}, 
title = {COSMIC: exploring the world's knowledge of somatic mutations in human cancer},
volume = {43}, 
number = {D1}, 
pages = {D805-D811}, 
year = {2015}, 
doi = {10.1093/nar/gku1075}, 
abstract ={COSMIC, the Catalogue Of Somatic Mutations In Cancer (http://cancer.sanger.ac.uk) is the world's largest and most comprehensive resource for exploring the impact of somatic mutations in human cancer. Our latest release (v70; Aug 2014) describes 2 002 811 coding point mutations in over one million tumor samples and across most human genes. To emphasize depth of knowledge on known cancer genes, mutation information is curated manually from the scientific literature, allowing very precise definitions of disease types and patient details. Combination of almost 20 000 published studies gives substantial resolution of how mutations and phenotypes relate in human cancer, providing insights into the stratification of mutations and biomarkers across cancer patient populations. Conversely, our curation of cancer genomes (over 12 000) emphasizes knowledge breadth, driving discovery of unrecognized cancer-driving hotspots and molecular targets. Our high-resolution curation approach is globally unique, giving substantial insight into molecular biomarkers in human oncology. In addition, COSMIC also details more than six million noncoding mutations, 10 534 gene fusions, 61 299 genome rearrangements, 695 504 abnormal copy number segments and 60 119 787 abnormal expression variants. All these types of somatic mutation are annotated to both the human genome and each affected coding gene, then correlated across disease and mutation types.}, 
URL = {http://nar.oxfordjournals.org/content/43/D1/D805.abstract}, 
eprint = {http://nar.oxfordjournals.org/content/43/D1/D805.full.pdf+html}, 
journal = {Nucleic Acids Research} 
}

@article{Smedley16,
abstract = {The interpretation of non-coding variants still constitutes a major challenge in the application of whole-genome sequencing in Mendelian disease, especially for single-nucleotide and other small non-coding variants. Here we present Genomiser, an analysis framework that is able not only to score the relevance of variation in the non-coding genome, but also to associate regulatory variants to specific Mendelian diseases. Genomiser scores variants through either existing methods such as CADD or a bespoke machine learning method and combines these with allele frequency, regulatory sequences, chromosomal topological domains, and phenotypic relevance to discover variants associated to specific Mendelian disorders. Overall, Genomiser is able to identify causal regulatory variants as the top candidate in 77{\%} of simulated whole genomes, allowing effective detection and discovery of regulatory variants in Mendelian disease.},
author = {Smedley, Damian and Schubach, Max and Jacobsen, Julius O.B. and K{\"{o}}hler, Sebastian and Zemojtel, Tomasz and Spielmann, Malte and J{\"{a}}ger, Marten and Hochheiser, Harry and Washington, Nicole L. and McMurry, Julie A. and Haendel, Melissa A. and Mungall, Christopher J. and Lewis, Suzanna E. and Groza, Tudor and Valentini, Giorgio and Robinson, Peter N.},
doi = {10.1016/j.ajhg.2016.07.005},
issn = {00029297},
journal = {The American Journal of Human Genetics},
month = {sep},
number = {3},
pages = {595--606},
publisher = {Elsevier},
title = {{A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease}},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0002929716302786},
volume = {99},
year = {2016}
}


@article{Saito15,
	Author = "Saito, T. and Rehmsmeier, M.",
	Journal = {PLoS ONE},
	Pages = {e0118432},
	Title = {The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets},
	Volume = {10},
	Year = {2015}
}

@inproceedings{Davis06,
 author = {Davis, Jesse and Goadrich, Mark},
 title = {The Relationship Between Precision-Recall and ROC Curves},
 booktitle = {Proceedings of the 23rd International Conference on Machine Learning},
 series = {ICML '06},
 year = {2006},
 isbn = {1-59593-383-2},
 location = {Pittsburgh, Pennsylvania, USA},
 pages = {233--240},
 numpages = {8},
 url = {http://doi.acm.org/10.1145/1143844.1143874},
 doi = {10.1145/1143844.1143874},
 acmid = {1143874},
 publisher = {ACM},
 address = {New York, NY, USA},
} 

@article{Fan08,
	Author = "Fan, R.E. and Chang, K.W. and Hsieh, C.J. and Wang, X.R. and Lin, C.J.",
	Journal = {Journal of Machine Learning Research},
	Pages = {1871--1874},
	Title = {LIBLINEAR: A library for large linear classification},
	Volume = {9},
	Year = {2008}
}


@INPROCEEDINGS{Die00a,
   author = "Dietterich, T.G.",
   title = "Ensemble Methods in Machine Learning",
   editor = "Kittler, J. and Roli, F.",
	 booktitle = "Multiple Classifier Systems. First International Workshop, MCS 2000, 
	 Cagliari, Italy", 
	 series="Lecture Notes in Computer Science",
   year = 2000,
	 volume="1857",
	 pages = "1--15",
   publisher = "Springer-Verlag"
   } 	
   
@INCOLLECTION{Vale12d,
   author = "Re, M. and Valentini, G.",
   title = "Ensemble methods: a review",
   booktitle = "Advances in Machine Learning and Data Mining for Astronomy", 
   year = 2012,
   series="Data Mining and Knowledge Discovery",
   pages = "563--594",
   publisher = "Chapman \& Hall"	 
   } 

@ARTICLE{Goldstein11,
author="Goldstein, BA and Polley, EC and Briggs, FBS",
journal={Statistical Applications in Genetics and Molecular Biology},
title={Random Forests for Genetic Association Studies},
year={2011},
volume={10},
number={1},
doi = {10.2202/1544-6115.1691}
}



@ARTICLE{Ritchie14b,
author="Ritchie, G.R. and Flicek, P.",
journal={Genome Med.},
title={Computational approaches to interpreting genomic sequence variation.},
year={2014},
volume={6},
number={87}
}



@article{Welter14,
author = {Welter, Danielle and MacArthur, Jacqueline and Morales, Joannella and Burdett, Tony and Hall, Peggy and Junkins, Heather and Klemm, Alan and Flicek, Paul and Manolio, Teri and Hindorff, Lucia and Parkinson, Helen}, 
title = {The NHGRI GWAS Catalog, a curated resource of SNP-trait associations},
volume = {42}, 
number = {D1}, 
pages = {D1001-D1006}, 
year = {2014}, 
doi = {10.1093/nar/gkt1229}, 
abstract ={The National Human Genome Research Institute (NHGRI) Catalog of Published Genome-Wide Association Studies (GWAS) Catalog provides a publicly available manually curated collection of published GWAS assaying at least 100 000 single-nucleotide polymorphisms (SNPs) and all SNP-trait associations with P <1 � 10\u22125. The Catalog includes 1751 curated publications of 11 912 SNPs. In addition to the SNP-trait association data, the Catalog also publishes a quarterly diagram of all SNP-trait associations mapped to the SNPs\u2019 chromosomal locations. The Catalog can be accessed via a tabular web interface, via a dynamic visualization on the human karyotype, as a downloadable tab-delimited file and as an OWL knowledge base. This article presents a number of recent improvements to the Catalog, including novel ways for users to interact with the Catalog and changes to the curation infrastructure.}, 
URL = {http://nar.oxfordjournals.org/content/42/D1/D1001.abstract}, 
eprint = {http://nar.oxfordjournals.org/content/42/D1/D1001.full.pdf+html}, 
journal = {Nucleic Acids Research} 
}

@Inbook{Ritchie2015,
author="Ritchie, G. and Flicek, P.",
editor="Zeggini, E.
and Morris, A.",
title="{Functional Annotation of Rare Genetic Variants}",
bookTitle="{Assessing Rare Variation in Complex Traits: Design and Analysis of Genetic Studies}",
year="2015",
publisher="Springer New York",
address="New York, NY",
pages="57--70",
isbn="978-1-4939-2824-8",
doi="10.1007/978-1-4939-2824-8_5",
url="http://dx.doi.org/10.1007/978-1-4939-2824-8_5"
}

@Article{Visscher2012,
  author               = {Visscher, Peter M and Brown, Matthew A and McCarthy, Mark I and Yang, Jian},
  title                = {Five years of GWAS discovery.},
  journal              = {American journal of human genetics},
  year                 = {2012},
  volume               = {90},
  pages                = {7--24},
  month                = {Jan},
  __markedentry        = {[robinp:6]},
  abstract             = {The past five years have seen many scientific and biological discoveries made through the experimental design of genome-wide association studies (GWASs). These studies were aimed at detecting variants at genomic loci that are associated with complex traits in the population and, in particular, at detecting associations between common single-nucleotide polymorphisms (SNPs) and common diseases such as heart disease, diabetes, auto-immune diseases, and psychiatric disorders. We start by giving a number of quotes from scientists and journalists about perceived problems with GWASs. We will then briefly give the history of GWASs and focus on the discoveries made through this experimental design, what those discoveries tell us and do not tell us about the genetics and biology of complex traits, and what immediate utility has come out of these studies. Rather than giving an exhaustive review of all reported findings for all diseases and other complex traits, we focus on the results for auto-immune diseases and metabolic diseases. We return to the perceived failure or disappointment about GWASs in the concluding section.},
  citation-subset      = {IM},
  completed            = {2012-03-12},
  copyright            = {Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.},
  country              = {United States},
  created              = {2012-01-16},
  doi                  = {10.1016/j.ajhg.2011.11.029},
  issn                 = {1537-6605},
  issn-linking         = {0002-9297},
  issue                = {1},
  journal-abbreviation = {Am J Hum Genet},
  keywords             = {Autoimmune Diseases, genetics; Female; Genetic Linkage; Genetic Loci; Genetic Predisposition to Disease; Genome-Wide Association Study, history, methods, trends; History, 21st Century; Humans; Male; Metabolic Diseases, genetics; Translational Medical Research},
  nlm                  = {PMC3257326},
  nlm-id               = {0370475},
  owner                = {NLM},
  pmid                 = {22243964},
  pubmodel             = {Print},
  pubstatus            = {ppublish},
  revised              = {2015-01-28},
  status               = {MEDLINE},
}

@article{Schubach17,
	Author = "Schubach, M. and Re, M. and Robinson, P.N. and Valentini, G.",
	Journal = {Scientific Reports},
	publisher="Nature Publishing",
	volume=7,
	number=2959,
	Title = {Imbalance-Aware Machine Learning for Predicting Rare and Common Disease-Associated Non-Coding Variants},
	doi= {10.1038/s41598-017-03011-5},
	Year = {2017}
}



@Comment{jabref-meta: databaseType:bibtex;}

