Sauer U., Heinemann M., Zamboni N., Getting closer to the whole picture Science 2007 316 5824 550 551
Gardner T. S., Faith J. J., Reverse-engineering transcription control networks Physics of Life Reviews 2005 2 1 65 88
Meyer P. E., Kontos K., Lafitte F., Bontempi G., Information-theoretic inference of large transcriptional regulatory networks EURASIP Journal on Bioinformatics and Systems Biology 2007 2007 9
Olsen C., Meyer P. M., Bontempi G., On the impact of entropy estimator in transcriptional regulatory network inference Proceedings of the 5th International Workshop on Computational Systems Biology (WCSB 08) June 2008 Leipzig, Germany
Margolin A. A., Nemenman I., Basso K., ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context BMC Bioinformatics 2006 7 supplement 1, article S7 1 15
Faith J. J., Hayete B., Thaden J. T., Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles PLoS Biology 2007 5 1, article e8 1 3
Van den Bulcke T., Van Leemput K., Naudts B., SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms BMC Bioinformatics 2006 7, article 43 1 12
Hausser J., Improving entropy estimation and the inference of genetic regulatory networks, M.S. thesis 2006 August Cedex, France Department of Biosciences, National Institute of Applied Sciences of Lyon
Steuer R., Kurths J., Daub C. O., Weise J., Selbig J., The mutual information: detecting and evaluating dependencies between variables Bioinformatics 2002 18 supplement 2 S231 S240
Paninski L., Estimation of entropy and mutual information Neural Computation 2003 15 6 1191 1253
Schfer J., Strimmer K., A shrinkage approach to large-scale covariance matrix estimation and implications for functional genomics Statistical Applications in Genetics and Molecular Biology 2005 4 1, article 32
Haykin S., Neural Networks: A Comprehensive Foundation 1999 Upper Saddle River, NJ, USA Prentice Hall
Dougherty J., Kohavi R., Sahami M., Supervised and unsupervised discretization of continuous features Proceedings of the 20th International Conference on Machine Learning (ICML 95) July 1995 Tahoe City, Calif, USA 194 202
Yang Y., Webb G. I., On why discretization works for nave-bayes classifiers Proceedings of the 16th Australian Joint Conference on Artificial Intelligence (AI 03) December 2003 Perth, Australia 440 452
Ding C., Peng H., Minimum redundancy feature selection from microarray gene expression data Journal of Bioinformatics and Computational Biology 2005 3 2 185 205
Cover T. M., Thomas J. A., Elements of Information Theory 1990 New York, NY, USA John Wiley Sons
Meyer P. E., Lafitte F., Bontempi G., minet: Mutual Information Network Inference. R package version 1.1.3
Sokolova M., Japkowicz N., Szpakowicz S., Beyond accuracy, f-score and roc: a family of discriminant measures for performance evaluation Proceedings of the AAAI Workshop on Evaluation Methods for Machine Learning July 2006 Boston, Mass, USA
DeRisi J. L., Iyer V. R., Brown P. O., Exploring the metabolic and genetic control of gene expression on a genomic scale Science 1997 278 5338 680 686
Chu S., DeRisi J., Eisen M., The transcriptional program of sporulation in budding yeast Science 1998 282 5389 699 705
Spellman P. T., Sherlock G., Zhang M. Q., Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization Molecular Biology of the Cell 1998 9 12 3273 3297
Ferea T. L., Botstein D., Brown P. O., Rosenzweig R. F., Systematic changes in gene expression patterns following adaptive evolution in yeast Proceedings of the National Academy of Sciences of the United States of America 1999 96 17 9721 9726
Gasch A. P., Spellman P. T., Kao C. M., Genomic expression programs in the response of yeast cells to environmental changes Molecular Biology of the Cell 2000 11 12 4241 4257
Gasch A. P., Huang M., Metzner S., Botstein D., Elledge S. J., Brown P. O., Genomic expression responses to DNA-damaging agents and the regulatory role of the yeast ATR homolog Mec1p Molecular Biology of the Cell 2001 12 10 2987 3003
Hughes T. R., Marton M. J., Jones A. R., Functional discovery via a compendium of expression profiles Cell 2000 102 1 109 126
Ogawa N., DeRisi J., Brown P. O., New components of a system for phosphate accumulation and polyphosphate metabolism in Saccharomyces cerevisiae revealed by genomic expression analysis Molecular Biology of the Cell 2000 11 12 4309 4321
Godard P., Urrestarazu A., Vissers S., Effect of 21 different nitrogen sources on global gene expression in the yeast Saccharomyces cerevisiae Molecular and Cellular Biology 2007 27 8 3065 3086
Buck M. J., Lieb J. D., ChIP-chip: considerations for the design, analysis, and application of genome-wide chromatin immunoprecipitation experiments Genomics 2004 83 3 349 360
Harbison C. T., Gordon D. B., Lee T. I., Transcriptional regulatory code of a eukaryotic genome Nature 2004 430 7004 99 104
Simonis N., Wodak S. J., Cohen G. N., van Helden J., Combining pattern discovery and discriminant analysis to predict gene co-regulation Bioinformatics 2004 20 15 2370 2379