HiPub: translating PubMed and PMC texts to networks for knowledge discovery
- Authors
- Lee, Kyubum; Shin, Wonho; Kim, Byounggun; Lee, Sunwon; Choi, Yonghwa; Kim, Sunkyu; Jeon, Minji; Tan, Aik Choon; Kang, Jaewoo
- Issue Date
- 15-9월-2016
- Publisher
- OXFORD UNIV PRESS
- Citation
- BIOINFORMATICS, v.32, no.18, pp.2886 - 2888
- Indexed
- SCIE
SCOPUS
- Journal Title
- BIOINFORMATICS
- Volume
- 32
- Number
- 18
- Start Page
- 2886
- End Page
- 2888
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/87523
- DOI
- 10.1093/bioinformatics/btw511
- ISSN
- 1367-4803
- 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.
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- Appears in
Collections - Graduate School > Department of Computer Science and Engineering > 1. Journal Articles
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