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 textmined 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.
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CITATION STYLE
Pilehvar, M. T., Bernard, A., Smedley, D., & Collier, N. (2022). PheneBank: a literature-based database of phenotypes. Bioinformatics, 38(4), 1179–1180. https://doi.org/10.1093/bioinformatics/btab740
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