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Bioinformatics. 2016 Sep 15;32(18):2886-8. doi: 10.1093/bioinformatics/btw511. Epub 2016 Aug 2.

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

Author information

1
Department of Computer Science and Engineering, Korea University, Seoul, Korea.
2
Interdisciplinary Graduate Program in Bioinformatics, Korea University, Seoul, Korea.
3
Translational Bioinformatics and Cancer Systems Biology Laboratory, Division of Medical Oncology, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
4
Department of Computer Science and Engineering, Korea University, Seoul, Korea Interdisciplinary Graduate Program in Bioinformatics, Korea University, Seoul, Korea.

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.

AVAILABILITY AND IMPLEMENTATION:

HiPub and detailed user guide are available at http://hipub.korea.ac.kr

CONTACT:

kangj@korea.ac.kr, aikchoon.tan@ucdenver.edu

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
27485446
PMCID:
PMC5018380
DOI:
10.1093/bioinformatics/btw511
[Indexed for MEDLINE]
Free PMC Article

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