LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support.

Authors

  • Axel J Soto
    National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester M1 7DN, UK.
  • Chrysoula Zerva
    National Centre for Text Mining, School of Computer Science.
  • Riza Batista-Navarro
  • Sophia Ananiadou