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HiPub: translating PubMed and PMC texts to networks for knowledge discovery

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dc.contributor.authorLee, Kyubum-
dc.contributor.authorShin, Wonho-
dc.contributor.authorKim, Byounggun-
dc.contributor.authorLee, Sunwon-
dc.contributor.authorChoi, Yonghwa-
dc.contributor.authorKim, Sunkyu-
dc.contributor.authorJeon, Minji-
dc.contributor.authorTan, Aik Choon-
dc.contributor.authorKang, Jaewoo-
dc.date.accessioned2021-09-03T20:03:10Z-
dc.date.available2021-09-03T20:03:10Z-
dc.date.created2021-06-16-
dc.date.issued2016-09-15-
dc.identifier.issn1367-4803-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/87523-
dc.description.abstractWe introduce HiPub, a seamless Chrome browser plug-in that automatically recognizes, annotates and translates biomedical entities from texts into networks for knowledge discovery. Using a combination of two different named-entity recognition resources, HiPub can recognize genes, proteins, diseases, drugs, mutations and cell lines in texts, and achieve high precision and recall. HiPub extracts biomedical entity-relationships from texts to construct context-specific networks, and integrates existing network data from external databases for knowledge discovery. It allows users to add additional entities from related articles, as well as user-defined entities for discovering new and unexpected entity-relationships. HiPub provides functional enrichment analysis on the biomedical entity network, and link-outs to external resources to assist users in learning new entities and relations.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherOXFORD UNIV PRESS-
dc.titleHiPub: translating PubMed and PMC texts to networks for knowledge discovery-
dc.typeArticle-
dc.contributor.affiliatedAuthorKang, Jaewoo-
dc.identifier.doi10.1093/bioinformatics/btw511-
dc.identifier.scopusid2-s2.0-84992187302-
dc.identifier.wosid000384651100030-
dc.identifier.bibliographicCitationBIOINFORMATICS, v.32, no.18, pp.2886 - 2888-
dc.relation.isPartOfBIOINFORMATICS-
dc.citation.titleBIOINFORMATICS-
dc.citation.volume32-
dc.citation.number18-
dc.citation.startPage2886-
dc.citation.endPage2888-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaBiotechnology & Applied Microbiology-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaMathematical & Computational Biology-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryBiochemical Research Methods-
dc.relation.journalWebOfScienceCategoryBiotechnology & Applied Microbiology-
dc.relation.journalWebOfScienceCategoryComputer Science, Interdisciplinary Applications-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
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