TY - JOUR
T1 - HiPub
T2 - Translating PubMed and PMC texts to networks for knowledge discovery
AU - Lee, Kyubum
AU - Shin, Wonho
AU - Kim, Byounggun
AU - Lee, Sunwon
AU - Choi, Yonghwa
AU - Kim, Sunkyu
AU - Jeon, Minji
AU - Tan, Aik Choon
AU - Kang, Jaewoo
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea. NRF- 2014M3C9A3063543 (to J.K.), NRF-2014R1A2A1A10051238 (to J.K.) and NRF-2015M3A9D7031070 (to J.K.), the National Institutes of Health P50CA058187 (to A.C.T.), P30CA046934 (to A.C.T.) and the David F. and Margaret T. Grohne Family Foundation (to A.C.T.).
Publisher Copyright:
© 2016 The Author. Published by Oxford University Press. All rights reserved.
PY - 2016/9/15
Y1 - 2016/9/15
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84992187302&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btw511
DO - 10.1093/bioinformatics/btw511
M3 - Article
C2 - 27485446
AN - SCOPUS:84992187302
SN - 1367-4803
VL - 32
SP - 2886
EP - 2888
JO - Bioinformatics
JF - Bioinformatics
IS - 18
ER -