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남덕우

Nam, Dougu
Bioinformatics Lab.
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dc.citation.endPage 3285 -
dc.citation.number 10 -
dc.citation.startPage 3283 -
dc.citation.title BIOINFORMATICS -
dc.citation.volume 36 -
dc.contributor.author Kim, Jinhwan -
dc.contributor.author Yoon, Sora -
dc.contributor.author Nam, Dougu -
dc.date.accessioned 2023-12-21T17:38:03Z -
dc.date.available 2023-12-21T17:38:03Z -
dc.date.created 2020-06-26 -
dc.date.issued 2020-05 -
dc.description.abstract A Summary: We present an R-Shiny package, netGO, for novel network-integrated pathway enrichment analysis. The conventional Fisher's exact test (FET) considers the extent of overlap between target genes and pathway gene-sets, while recent network-based analysis tools consider only network interactions between the two. netGO implements an intuitive framework to integrate both the overlap and networks into a single score, and adaptively resamples genes based on network degrees to assess the pathway enrichment. In benchmark tests for gene expression and genome-wide association study (GWAS) data, netGO captured the relevant gene-sets better than existing tools, especially when analyzing a small number of genes. Specifically, netGO provides user-interactive visualization of the target genes, enriched gene-set and their network interactions for both netGO and FET results for further analysis. For this visualization, we also developed a standalone R-Shiny package shinyCyJS to connect R-shiny and the JavaScript version of cytoscape. -
dc.identifier.bibliographicCitation BIOINFORMATICS, v.36, no.10, pp.3283 - 3285 -
dc.identifier.doi 10.1093/bioinformatics/btaa077 -
dc.identifier.issn 1367-4803 -
dc.identifier.scopusid 2-s2.0-85084692775 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/33025 -
dc.identifier.url https://academic.oup.com/bioinformatics/article/36/10/3283/5728635 -
dc.identifier.wosid 000537447900054 -
dc.language 영어 -
dc.publisher OXFORD UNIV PRESS -
dc.title netGO: R-Shiny package for network-integrated pathway enrichment analysis -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability -
dc.relation.journalResearchArea Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology; Computer Science; Mathematical & Computational Biology; Mathematics -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordPlus FUNCTIONAL GENE NETWORKS -
dc.subject.keywordPlus DATABASE -
dc.subject.keywordPlus V2 -

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