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Discovery of biological networks from diverse functional genomic data

Chad L Myers12, Drew Robson3, Adam Wible1, Matthew A Hibbs12, Camelia Chiriac2, Chandra L Theesfeld4, Kara Dolinski2 and Olga G Troyanskaya12*

Author affiliations

1 Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08544, USA

2 Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, NJ 08544, USA

3 Department of Mathematics, Princeton University, Washington Road, Princeton, NJ 08540, USA

4 Department of Genetics, School of Medicine, Mailstop-S120, Stanford University, Stanford, CA 94305-5120, USA

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Citation and License

Genome Biology 2005, 6:R114  doi:10.1186/gb-2005-6-13-r114

Published: 19 December 2005

Abstract

We have developed a general probabilistic system for query-based discovery of pathway-specific networks through integration of diverse genome-wide data. This framework was validated by accurately recovering known networks for 31 biological processes in Saccharomyces cerevisiae and experimentally verifying predictions for the process of chromosomal segregation. Our system, bioPIXIE, a public, comprehensive system for integration, analysis, and visualization of biological network predictions for S. cerevisiae, is freely accessible over the worldwide web.