New visual data mining tools for systems biology
Vincent VanBuren, PhD
Department of Systems Biology and Translational Medicine
Texas A & M HSC College of Medicine
Effective treatment of disease in the much-anticipated future of personalized medicine will rely on efforts to characterize the systems biology of affected tissues. We have previously developed a tool that identifies small correlation networks around a gene of interest from publicly available mouse microarray data. This tool, StarNet (http://vanburenlab.tamhsc.edu/starnet.html), uses a “guilt by association” approach to identify groups of genes that are putatively enriched for genes that have a biological interaction with a gene of interest. We have more recently developed Cognoscente, a new Web-based interface to a database of known interactions. The novelty of Cognoscente is that it draws known interaction networks from multiple provided gene IDs, and can draw multi-species networks of genes grouped by Homologene IDs. The database has an additional interface for user submissions of interactions. As such, Cognoscente provides inherent support for all organisms catalogued with Entrez Gene IDs. Submissions are reviewed and go through a documented approval pipeline, but all submissions go live immediately in Cognoscente with a status of ‘submitted’. Cognoscente currently contains interaction data for more than 20 organisms, including human, mouse, rat, S. cerevisiae, C. elegans, D. melanogaster, and S. pombe, with a total of over 300,000 entries.