PheneBank: a literature-based database of phenotypes.
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Publication Date
2022-01-27Journal Title
Bioinformatics
ISSN
1367-4803
Publisher
Oxford University Press (OUP)
Language
eng
Type
Article
This Version
AM
Metadata
Show full item recordCitation
Pilehvar, M. T., Bernard, A., Smedley, D., & Collier, N. (2022). PheneBank: a literature-based database of phenotypes.. Bioinformatics https://doi.org/10.1093/bioinformatics/btab740
Abstract
MOTIVATION: Significant effort has been spent by curators to create coding systems for phenotypes such as the Human Phenotype Ontology, as well as disease-phenotype annotations. We aim to support the discovery of literature-based phenotypes and integrate them into the knowledge discovery process. RESULTS: PheneBank is a Web-portal for retrieving human phenotype-disease associations that have been text-mined from the whole of Medline. Our approach exploits state-of-the-art machine learning for concept identification by utilizing an expert annotated rare disease corpus from the PMC Text Mining subset. Evaluation of the system for entities is conducted on a gold-standard corpus of rare disease sentences and for associations against the Monarch initiative data. AVAILABILITY AND IMPLEMENTATION: The PheneBank Web-portal freely available at http://www.phenebank.org. Annotated Medline data is available from Zenodo at DOI: 10.5281/zenodo.1408800. Semantic annotation software is freely available for non-commercial use at GitHub: https://github.com/pilehvar/phenebank. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Sponsorship
Medical Research Council (grant MR/M025160/1).
Funder references
Engineering and Physical Sciences Research Council (EP/M005089/1)
Medical Research Council (MR/M025160/1)
Identifiers
External DOI: https://doi.org/10.1093/bioinformatics/btab740
This record's URL: https://www.repository.cam.ac.uk/handle/1810/329879
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