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

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

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.

MeSH terms

  • Algorithms
  • Computational Biology / methods
  • Data Curation*
  • Databases, Factual*
  • Genes
  • Humans
  • Pattern Recognition, Automated*
  • Pharmaceutical Preparations
  • Proteins
  • PubMed
  • Search Engine

Substances

  • Pharmaceutical Preparations
  • Proteins