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Bioinformatics Vol. 17 no. 90001 2001
Pages S215-S224
© 2001 Oxford University Press

Inferring subnetworks from perturbed expression profiles

Dana Pe’er 1, Aviv Regev 2,3, Gal Elidan 1 and Nir Friedman 1

1 School of Computer Science & Engineering, Hebrew University, Jerusalem, 91904, Israel
2 Department of Cell Research and Immunology, Life Sciences Faculty, Tel Aviv University, Tel Aviv, 69978, Israel
3 Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, 76100, Israel

Received on February 6, 2001 ; revised on April 3, 2001 ; accepted on April 3, 2001

Genome-wide expression profiles of genetic mutants provide a wide variety of measurements of cellular responses to perturbations. Typical analysis of such data identifies genes affected by perturbation and uses clustering to group genes of similar function. In this paper we discover a finer structure of interactions between genes, such as causality, mediation, activation, and inhibition by using a Bayesian network framework. We extend this framework to correctly handle perturbations, and to identify significant subnetworks of interacting genes. We apply this method to expression data of S. cerevisiae mutants and uncover a variety of structured metabolic, signaling and regulatory pathways.

Contact: danab{at}cs.huji.ac.il


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