One of the fundamental features of a complex network is the notion of community, which can be defined as a group of nodes that are more densely connected with each other than they are to the rest of the network.
#CYTOSCAPE SOFTWARE SOFTWARE#
This is a PLOS Computational Biology Software paper. The terms of these arrangements have been reviewed and approved by the University of California San Diego in accordance with its conflict of interest policies. TI is on the Scientific Advisory Board of Ideaya BioSciences, Inc., has an equity interest and receives sponsored research funding. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: TI is co-founder of Data4Cure, Inc., is on the Scientific Advisory Board, and has an equity interest. Additional data URLs are provided in the Supporting Information files.įunding: This work was supported by the National Institutes of Health (R01 HG009979, P41 GM103504). This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.ĭata Availability: All relevant data are within the manuscript and its Supporting Information files. Received: ApAccepted: AugPublished: October 23, 2020Ĭopyright: © 2020 Singhal et al. Przytycka, National Center for Biotechnology Information (NCBI), UNITED STATES PLoS Comput Biol 16(10):Įditor: Teresa M. (2020) Multiscale community detection in Cytoscape. We demonstrate that the CDAPS framework can be applied to high-throughput protein-protein interaction networks to gain novel insights, such as the identification of putative new members of known protein complexes.Ĭitation: Singhal A, Cao S, Churas C, Pratt D, Fortunato S, Zheng F, et al. With novel design principles, CDAPS addresses unmet new challenges, such as identifying hierarchical community structures, comparison of outputs generated from diverse network resources, and easy deployment of new algorithms, to facilitate community-sourced science. Here we present a service-oriented, end-to-end software framework, CDAPS (Community Detection APplication and Service), that integrates the identification, annotation, visualization, and interrogation of multiscale network communities, accessible within the popular Cytoscape network analysis platform. This recent impact creates a need to make these techniques and their accompanying visualization schemes available to a broad range of biologists. Detection of community structure has become a fundamental step in the analysis of biological networks with application to protein function annotation, disease gene prediction, and drug discovery.
0 kommentar(er)
