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

  • Authors:
  • Boon-Siew Seah;Sourav Bhowmick;Charles Forbes Dewey, Jr.;Hanry Yu

  • Affiliations:
  • Nanyang Technological University, Singapore, Singapore;Nanyang Technological University, Singapore, Singapore;Massachusetts Institute of Technology, Cambridge, MA, USA;National University of Singapore, Singapore, Singapore

  • Venue:
  • Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
  • Year:
  • 2012

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Abstract

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.