Better Network Modules: New Tools for Protein Network Analysis

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"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."The University of Maryland College Park is awarded a grant to develop new algorithms and a suite of software tools based on a general and flexible definition of a "network module" in order to extract meaningful biological clusters from noisy and incomplete protein-protein interaction data. Recently developed high-throughput techniques are being used to sample protein-protein interactions from many organisms and are creating a wealth of data that must be analyzed computationally. A central challenge in the study of these networks is finding biologically meaningful and interpretable modules within them. The new tools and algorithms will be used to improve visualization of protein interaction networks, identify protein complexes and biological processes embedded within the network data, and to discover redundant pathways from synthetic lethal interaction data. They will also be applied to comparing the interaction networks of several different species. The resulting network analysis software will expand the capabilities of both systems biologists and biologists working on particular protein complexes and pathways to make better use of noisy network data, and the proposed visualization software will vastly improve researchers? capability to interactively explore these networks. A public database will be created to curate computationally predicted annotations made by this, and other, projects using this method. The work will strengthen understanding of the organization of biological networks, and it will have broader impact by increasing the information technology infrastructure available for the analysis of interaction data, providing better transfer of hypotheses between computational biologists and biologists, and by the training of undergraduates in a summer internship program. Information about the project and how to access the database and software will be available at the project website http://www.cbcb.umd.edu/research/bionet/.