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

Authors
Lee, KyubumShin, WonhoKim, ByounggunLee, SunwonChoi, YonghwaKim, SunkyuJeon, MinjiTan, Aik ChoonKang, 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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