Towards pathway curation through literature mining - A case study using PharmGKB

K. E. Ravikumar, Kavishwar B. Wagholikar, Hongfang Liu

Research output: Contribution to journalConference article

9 Scopus citations

Abstract

The creation of biological pathway knowledge bases is largely driven by manual effort to curate based on evidences from the scientific literature. It is highly challenging for the curators to keep up with the literature. Text mining applications have been developed in the last decade to assist human curators to speed up the curation pace where majority of them aim to identify the most relevant papers for curation with little attempt to directly extract the pathway information from text. In this paper, we describe a rule-based literature mining system to extract pathway information from text. We evaluated the system using curated pharmacokinetic (PK) and pharmacodynamic (PD) pathways in PharmGKB. The system achieved an F-measure of 63.11% and 34.99% for entity extraction and event extraction respectively against all PubMed abstracts cited in PharmGKB. It may be possible to improve the system performance by incorporating using statistical machine learning approaches. This study also helped us gain insights into the barriers towards automated event extraction from text for pathway curation.

Original languageEnglish (US)
Pages (from-to)352-363
Number of pages12
JournalPacific Symposium on Biocomputing
StatePublished - Jan 1 2014
Event19th Pacific Symposium on Biocomputing, PSB 2014 - Kohala Coast, United States
Duration: Jan 3 2014Jan 7 2014

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computational Theory and Mathematics

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