Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations, Bernoulli, vol.10, issue.6, pp.989-1010, 2004. ,
DOI : 10.3150/bj/1106314847
Incorporating pathway information into boosting estimation of high-dimensional risk prediction models, BMC Bioinformatics, vol.10, issue.1, p.18, 2009. ,
DOI : 10.1186/1471-2105-10-18
Over-optimism in bioinformatics research, Bioinformatics, vol.26, issue.3, pp.437-439, 2010. ,
DOI : 10.1093/bioinformatics/btp648
Optimal classifier selection and negative bias in error rate estimation: an empirical study on high-dimensional prediction, BMC Medical Research Methodology, vol.98, issue.1, p.85, 2009. ,
DOI : 10.1093/jnci/djj329
Evaluating microarray-based classifiers: an overview, Cancer Informatics, vol.6, pp.77-97, 2008. ,
Is cross-validation valid for small-sample microarray classification?, Bioinformatics, vol.20, issue.3, pp.374-380, 2004. ,
DOI : 10.1093/bioinformatics/btg419
Reducing the probability of false positive research findings by pre-publication validation ??? Experience with a large multiple sclerosis database, BMC Medical Research Methodology, vol.190, issue.1, p.18, 2008. ,
DOI : 10.1016/j.jneuroim.2007.07.011
On the optimality of the simple bayesian classifier under zero-one loss, Machine Learning, vol.29, issue.2/3, pp.103-130, 1997. ,
DOI : 10.1023/A:1007413511361
Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data, Journal of the American Statistical Association, vol.97, issue.457, pp.77-87, 2002. ,
DOI : 10.1198/016214502753479248
Stein's Paradox in Statistics, Scientific American, vol.236, issue.5, pp.119-127, 1977. ,
DOI : 10.1038/scientificamerican0577-119
Regularized Discriminant Analysis, Journal of the American Statistical Association, vol.33, issue.405, pp.165-175, 1989. ,
DOI : 10.1080/01621459.1989.10478752
Graph-constrained discriminant analysis of functional genomics data, 2008 IEEE International Conference on Bioinformatics and Biomeidcine Workshops, 2008. ,
DOI : 10.1109/BIBMW.2008.4686237
URL : https://hal.archives-ouvertes.fr/hal-00346450
Regularized linear discriminant analysis and its application in microarrays, Biostatistics, vol.8, issue.1, pp.86-100, 2007. ,
DOI : 10.1093/biostatistics/kxj035
Incorporating prior probabilities into high-dimensional classifiers, Biometrika, vol.97, issue.1, pp.31-48, 2010. ,
DOI : 10.1093/biomet/asp081
KEGG: Kyoto Encyclopedia of Genes and Genomes, Nucleic Acids Research, vol.28, issue.1, pp.27-30, 2000. ,
DOI : 10.1093/nar/28.1.27
Improved estimation of the covariance matrix of stock returns with an application to portfolio selection, Journal of Empirical Finance, vol.10, issue.5, pp.603-621, 2003. ,
DOI : 10.1016/S0927-5398(03)00007-0
Honey, I Shrunk the Sample Covariance Matrix, The Journal of Portfolio Management, vol.30, issue.4, pp.110-119, 2004. ,
DOI : 10.3905/jpm.2004.110
Network-constrained regularization and variable selection for analysis of genomic data, Bioinformatics, vol.24, issue.9, pp.1175-1182, 2008. ,
DOI : 10.1093/bioinformatics/btn081
A generalized inverse for matrices, Mathematical Proceedings of the Cambridge Philosophical Society, vol.11, issue.03, pp.406-413, 1955. ,
DOI : 10.1093/qmath/2.1.189
Classification of microarray data using gene networks, BMC Bioinformatics, vol.8, issue.1, p.35, 2007. ,
DOI : 10.1186/1471-2105-8-35
URL : https://hal.archives-ouvertes.fr/hal-00433577
Papers on normalization, variable selection, classification or clustering of microarray data, Bioinformatics, vol.25, issue.6, pp.701-702, 2009. ,
DOI : 10.1093/bioinformatics/btp038
A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics, Statistical Applications in Genetics and Molecular Biology, vol.4, issue.1, 2005. ,
DOI : 10.2202/1544-6115.1175
Gene expression correlates of clinical prostate cancer behavior, Cancer Cell, vol.1, issue.2, pp.203-209, 2002. ,
DOI : 10.1016/S1535-6108(02)00030-2
Feature selection guided by structural information, The Annals of Applied Statistics, vol.4, issue.2, 2010. ,
DOI : 10.1214/09-AOAS302SUPP
Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments, Statistical Applications in Genetics and Molecular Biology, vol.3, issue.1, 2004. ,
DOI : 10.2202/1544-6115.1027
Inadmissibility of the usual estimator for the mean of a multivariate normal distribution, Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, 1955. ,
Incorporating prior knowledge of gene functional groups into regularized discriminant analysis of microarray data, Bioinformatics, vol.23, issue.23, pp.3170-3177, 2007. ,
DOI : 10.1093/bioinformatics/btm488
Incorporating prior knowledge of predictors into penalized classifiers with multiple penalty terms, Bioinformatics, vol.23, issue.14, pp.1775-1782, 2007. ,
DOI : 10.1093/bioinformatics/btm234
Diagnosis of multiple cancer types by shrunken centroids of gene expression, Proceedings of the National Academy of Sciences 99, pp.6567-6572, 2002. ,
DOI : 10.1073/pnas.082099299
Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer, The Lancet, vol.365, issue.9460, pp.671-679, 2005. ,
DOI : 10.1016/S0140-6736(05)70933-8
Classification and biomarker identification using gene network modules and support vector machines, BMC Bioinformatics, vol.10, issue.1, p.337, 2009. ,
DOI : 10.1186/1471-2105-10-337
Reporting bias when using real data sets to analyze classification performance, Bioinformatics, vol.26, issue.1, pp.68-76, 2010. ,
DOI : 10.1093/bioinformatics/btp605