Discovery of biological networks from diverse functional genomic data

Chad L Myers¹^,2 , Drew Robson³ , Adam Wible¹ , Matthew A Hibbs¹^,2 , Camelia Chiriac² , Chandra L Theesfeld⁴ , Kara Dolinski² and Olga G Troyanskaya¹^,2

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

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

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

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

author email corresponding author email

Genome Biology 2005, 6:R114doi:10.1186/gb-2005-6-13-r114


Published:	19 December 2005

Subject areas: Bioinformatics, Genome studies, Cell biology

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.