TY - JOUR T1 - A Scalable Approach for Discovering Conserved Active Subnetworks across Species A1 - Deshpande, Raamesh A1 - Sharma, Shikha A1 - Verfaillie, Catherine M. A1 - Hu, Wei-Shou A1 - Myers, Chad L. Y1 - 2010/12/09 N2 - Author Summary Microarrays are a powerful tool for discovering genes whose expression is associated with a particular biological process or phenotype. Differential expression analysis can often generate a list of several hundred or even thousands of significant genes. While these genes represent real expression differences, the large number of candidates can make the process of hypothesis generation for further experimental studies challenging. Use of complementary datasets such as protein-protein interactions can help filter such candidate lists to genes involved with the most relevant pathways. This approach has been applied successfully by many groups, but to date, no one has developed an approach for discovering active pathways or subnetworks that are conserved across multiple species. We propose an algorithm, neXus (Network – cross(X)-species – Search), for cross-species active subnetwork discovery given candidate gene lists from two species and weighted protein-protein interaction networks. We validate our approach on expression studies from human and mouse stem cells. We find many active subnetworks that are conserved across species relevant to stem cell biology as well as other subnetworks that show species-specific behavior. We show that these networks are not likely to have been discovered by chance and discuss several specific cases that reveal potentially novel stem cell biology. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 6 IS - 12 UR - https://doi.org/10.1371/journal.pcbi.1001028 SP - e1001028 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1001028 ER -