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

Boon-Siew Seah, S. Bhowmick, C. F. Dewey, Hanry Yu
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引用次数: 0

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.
FUSE:一个数据驱动的蛋白质相互作用网络多层次功能总结系统
尽管近年来在高通量实验研究方面取得了进展,但鉴于大型蛋白质相互作用网络(PPI)的规模和高维性,系统级可视化和分析仍然是一项具有挑战性的任务。具体来说,仍然缺乏以多种分辨率自动抽象和总结ppi以提供其功能景观的高级视图的技术。在这个演示中,我们提出了一个新的数据驱动和通用系统,称为FUSE(功能摘要生成器),它生成不同组织级别的PPI的功能图,从广泛的过程-过程级交互到深入的复杂-复杂级交互。通过同时评估交互和注释数据,FUSE通过减少底层PPI的细节来抽象高阶交互图,形成相互连接的功能集群的功能汇总图。我们展示了FUSE的各种创新功能,这些功能可以帮助用户以用户友好的方式可视化这些摘要,并在复杂的ppi中导航。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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