-
- 1
-
A. Alizadeh, M.B. Eisen, R.E. Davis, C. Ma, I.S. Lossos, A. Rosenwald, J.C.
Boldrick, H. Sabet, T. Tran, X. Yu, J.I. Powell, L. Yang, G.E. Marti,
T. Moore, J. Hudson, L. Lu, D.B. Lewis, R. Tibshirani, G. Sherlock, W.C.
Chan, T.C. Greiner, D.D. Weisenburger, J.O. Armitage, R. Warnke, R. Levy,
W. Wilson, M.R. Grever, J.C. Byrd, D. Botstein, P.O. Brown, and L.M. Staudt.
Distinct types of diffuse large B-cell lymphoma identified by gene
expression profiling.
Nature, 403:503-511, 2000.
- 2
-
N. Alon and R. Boppana.
The monotone circuit complexity of boolean functions.
Combinatorica, 7(1):1-22, 1987.
- 3
-
Alon, U. et al.
Broad patterns of gene expressions revealed by clustering analysis of
tumor and normal colon tissues probed by oligonucleotide arrays.
PNAS, 96:6745-6750, 1999.
- 4
-
E. Amaldi and V. Kann.
On the approximation of minimizing non zero variables or unsatisfied
relations in linear systems.
Theoretical Computer Science, 209:237-260, 1998.
- 5
-
M. Ben-Or and N. Linial.
Collective coin flipping.
In Randomness and Computation, pages 91-115. Academic Press,
New York, 1990.
- 6
-
I. Benjamini, G. Kalai, and O. Schramm.
Noise sensitivity of boolean functions and applications to
percolation.
Publications Mathematiques de L'IHES, 90(1):5-43, 1999.
- 7
-
T.R. Golub et al.
Molecular Classification of Cancer: Class Discovery and
Class Prediction by Gene Expression Monitoring.
Science, 286:531-537, 1999.
- 8
-
I. Guyon, J. Weston, S. Barnhill, and V. Vapnik.
Gene Selection for Cancer Classification using Support
Vector Machines.
Machine Learning, 46(1/3):389-422, 2002.
- 9
-
C. Lai, M Reinders, L. van't Veer, and L. Wessels.
A protocol for building and evaluating predictors of disease state
based on microarray data.
BMC Bioinformatics, 7(235), 2006.
- 10
-
F. Li, , and Y. Yang.
Analysis of recursive gene selection approaches from microarray data.
Bioinformatics, 21(19):3741-3747, 2005.
- 11
-
X. Qiu, Y. Xiao, A. Gordon, and A. Yakovlev.
Assessing stability of gene selection in microarray data analysis.
BMC Bioinformatics, 7(50), 2006.
- 12
-
M. Shipp, K. Ross, P. Tamayo, A. Weng, J. Kutok, R. Aguiar, M. Gaasenbeek,
M. Angelo, M. Reich, G. Pinkus, T. Ray, M. Koval, K. Last, A. Norton,
T. Lister, J. Mesirov, D. Neuberg, E. Lander, J. Aster, and T. Golub.
Diffuse large B-cell lymphoma outcome prediction by gene-expression
profiling and supervised machine learning.
Nature Medicine, 8(1):68-74, 2002.