HiPub: translating PubMed and PMC texts to networks for knowledge discovery
DC Field | Value | Language |
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dc.contributor.author | Lee, Kyubum | - |
dc.contributor.author | Shin, Wonho | - |
dc.contributor.author | Kim, Byounggun | - |
dc.contributor.author | Lee, Sunwon | - |
dc.contributor.author | Choi, Yonghwa | - |
dc.contributor.author | Kim, Sunkyu | - |
dc.contributor.author | Jeon, Minji | - |
dc.contributor.author | Tan, Aik Choon | - |
dc.contributor.author | Kang, Jaewoo | - |
dc.date.accessioned | 2021-09-03T20:03:10Z | - |
dc.date.available | 2021-09-03T20:03:10Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2016-09-15 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/87523 | - |
dc.description.abstract | We 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.language | English | - |
dc.language.iso | en | - |
dc.publisher | OXFORD UNIV PRESS | - |
dc.title | HiPub: translating PubMed and PMC texts to networks for knowledge discovery | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Jaewoo | - |
dc.identifier.doi | 10.1093/bioinformatics/btw511 | - |
dc.identifier.scopusid | 2-s2.0-84992187302 | - |
dc.identifier.wosid | 000384651100030 | - |
dc.identifier.bibliographicCitation | BIOINFORMATICS, v.32, no.18, pp.2886 - 2888 | - |
dc.relation.isPartOf | BIOINFORMATICS | - |
dc.citation.title | BIOINFORMATICS | - |
dc.citation.volume | 32 | - |
dc.citation.number | 18 | - |
dc.citation.startPage | 2886 | - |
dc.citation.endPage | 2888 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Biotechnology & Applied Microbiology | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Biochemical Research Methods | - |
dc.relation.journalWebOfScienceCategory | Biotechnology & Applied Microbiology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
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