FUSE : a system for data-driven multi-level functional summarization of protein interaction networks

• Main Authors: Seah, Boon-Siew, Dewey Jr., C. Forbes, Yu, Hanry, Bhowmick, Sourav S.
• Other Authors: School of Computer Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
• Online Access: https://hdl.handle.net/10356/107171; http://hdl.handle.net/10220/16669
• Institution: Nanyang Technological University

Despite recent progress in high-throughput experimental studies, systems level visualization and analysis of large protein interaction networks (PPI) remains a challenging task, given its scale and high-dimensionality. Specifically, techniques that automatically abstract and summarize PPIs at multiple resolutions to provide high level views of its functional landscape are still lacking. In this demonstration, we present a novel data-driven and generic system called FUSE (Functional Summary Generator) that generates functional maps of a PPI at different levels of organization, from broad process-process level interactions to in-depth complex-complex level interactions. By simultaneously evaluating interaction and annotation data, FUSE abstracts higher-order interaction maps by reducing the details of the underlying PPI to form a functional summary graph of interconnected functional clusters. We demonstrate various innovative features of FUSE which aid users to visualize these summaries in a user-friendly manner and navigate through complex PPIs.