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Gilda: biomedical entity text normalization with machine-learned disambiguation as a service

View ORCID ProfileBenjamin M. Gyori, View ORCID ProfileCharles Tapley Hoyt, View ORCID ProfileAlbert Steppi
doi: https://doi.org/10.1101/2021.09.10.459803
Benjamin M. Gyori
1Laboratory of Systems Pharmacology, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115
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  • For correspondence: benjamin_gyori@hms.harvard.edu
Charles Tapley Hoyt
1Laboratory of Systems Pharmacology, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115
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Albert Steppi
1Laboratory of Systems Pharmacology, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115
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  • ORCID record for Albert Steppi
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Abstract

Summary Gilda is a software tool and web service which implements a scored string matching algorithm for names and synonyms across entries in biomedical ontologies covering genes, proteins (and their families and complexes), small molecules, biological processes and diseases. Gilda integrates machine-learned disambiguation models to choose between ambiguous strings given relevant surrounding text as context, and supports species-prioritization in case of ambiguity.

Availability The Gilda web service is available at http://grounding.indra.bio with source code, documentation and tutorials are available via https://github.com/indralab/gilda.

Contact benjamin_gyori{at}hms.harvard.edu

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • http://grounding.indra.bio

  • https://github.com/indralab/gilda

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted September 11, 2021.
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Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
Benjamin M. Gyori, Charles Tapley Hoyt, Albert Steppi
bioRxiv 2021.09.10.459803; doi: https://doi.org/10.1101/2021.09.10.459803
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Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
Benjamin M. Gyori, Charles Tapley Hoyt, Albert Steppi
bioRxiv 2021.09.10.459803; doi: https://doi.org/10.1101/2021.09.10.459803

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