Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

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

Full metadata record
DC Field Value Language
dc.contributor.authorSaha, Ashis-
dc.contributor.authorJeon, Minji-
dc.contributor.authorTan, Aik Choon-
dc.contributor.authorKang, Jaewoo-
dc.date.accessioned2021-09-04T14:20:14Z-
dc.date.available2021-09-04T14:20:14Z-
dc.date.created2021-06-16-
dc.date.issued2015-07-06-
dc.identifier.issn1932-6203-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/93030-
dc.description.abstractPathway 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.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherPUBLIC LIBRARY SCIENCE-
dc.subjectKNOWLEDGE-
dc.titleiCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data-
dc.typeArticle-
dc.contributor.affiliatedAuthorTan, Aik Choon-
dc.contributor.affiliatedAuthorKang, Jaewoo-
dc.identifier.doi10.1371/journal.pone.0131656-
dc.identifier.scopusid2-s2.0-84940386984-
dc.identifier.wosid000358157600119-
dc.identifier.bibliographicCitationPLOS ONE, v.10, no.7-
dc.relation.isPartOfPLOS ONE-
dc.citation.titlePLOS ONE-
dc.citation.volume10-
dc.citation.number7-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalWebOfScienceCategoryMultidisciplinary Sciences-
dc.subject.keywordPlusKNOWLEDGE-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Informatics > Department of Computer Science and Engineering > 1. Journal Articles
Graduate School > Department of Computer Science and Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kang, Jae woo photo

Kang, Jae woo
컴퓨터학과
Read more

Altmetrics

Total Views & Downloads

BROWSE