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iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data

Authors
Saha, AshisJeon, MinjiTan, Aik ChoonKang, Jaewoo
Issue Date
6-7월-2015
Publisher
PUBLIC LIBRARY SCIENCE
Citation
PLOS ONE, v.10, no.7
Indexed
SCIE
SCOPUS
Journal Title
PLOS ONE
Volume
10
Number
7
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/93030
DOI
10.1371/journal.pone.0131656
ISSN
1932-6203
Abstract
Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference.
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College of Informatics > Department of Computer Science and Engineering > 1. Journal Articles
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