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Bioinformatics Vol. 18 no. 90001 2002
Pages S258-S267
© 2002 Oxford University Press

Minreg: Inferring an active regulator set

Dana Pe'er 1, Aviv Regev 2,3 and Amos Tanay 4

1 School of Computer Science & Engineering, Hebrew University of Jerusalem
2 Department of Cell Research and Immunology, Life Sciences Faculty, Tel Aviv University
3 Department of Computer Science and Applied Mathematics, Weizmann Institute of Science
4 School of Computer Science, Tel Aviv University

Received on January 24, 2002 ; revised on April 1, 2002 ; accepted on April 1, 2002

Regulatory relations between genes are an important component of molecular pathways. Here, we devise a novel global method that uses a set of gene expression profiles to find a small set of relevant active regulators, identify the genes that they regulate, and automatically annotate them. We show that our algorithm is capable of handling a large number of genes in a short time and is robust to a wide range of parameters. We apply our method to a combined dataset of S. cerevisiae expression profiles, and validate the resulting model of regulation by cross-validation and extensive biological analysis of the selected regulators and their derived annotations.

Keywords: gene expression; gene regulation; gene networks; machine learning.


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