LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models
Abstract
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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Dec 08, 2017
- Source ID
- 10.1093/bioinformatics/btx774
Entities
People
- Axel J. Soto
- Chrysoula Zerva
- Riza Batista-navarro
- Sophia Ananiadou
Organizations
- Defense Advanced Research Projects Agency
- Engineering and Physical Sciences Research Council
- University of Manchester