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.
Bibliographical noteFunding 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.).
© 2016 The Author. Published by Oxford University Press. All rights reserved.
ASJC Scopus subject areas
- Statistics and Probability
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics