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

SUMMARY: Gilda is a software tool and web service that 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 machin...

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Detalles Bibliográficos
Autores principales: Gyori, Benjamin M, Hoyt, Charles Tapley, Steppi, Albert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710686/
https://www.ncbi.nlm.nih.gov/pubmed/36699362
http://dx.doi.org/10.1093/bioadv/vbac034
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author Gyori, Benjamin M
Hoyt, Charles Tapley
Steppi, Albert
author_facet Gyori, Benjamin M
Hoyt, Charles Tapley
Steppi, Albert
author_sort Gyori, Benjamin M
collection PubMed
description SUMMARY: Gilda is a software tool and web service that 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 AND IMPLEMENTATION: The Gilda web service is available at http://grounding.indra.bio with source code, documentation and tutorials available via https://github.com/indralab/gilda. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online.
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spelling pubmed-97106862023-01-24 Gilda: biomedical entity text normalization with machine-learned disambiguation as a service Gyori, Benjamin M Hoyt, Charles Tapley Steppi, Albert Bioinform Adv Application Note SUMMARY: Gilda is a software tool and web service that 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 AND IMPLEMENTATION: The Gilda web service is available at http://grounding.indra.bio with source code, documentation and tutorials available via https://github.com/indralab/gilda. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online. Oxford University Press 2022-05-11 /pmc/articles/PMC9710686/ /pubmed/36699362 http://dx.doi.org/10.1093/bioadv/vbac034 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Application Note
Gyori, Benjamin M
Hoyt, Charles Tapley
Steppi, Albert
Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
title Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
title_full Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
title_fullStr Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
title_full_unstemmed Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
title_short Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
title_sort gilda: biomedical entity text normalization with machine-learned disambiguation as a service
topic Application Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9710686/
https://www.ncbi.nlm.nih.gov/pubmed/36699362
http://dx.doi.org/10.1093/bioadv/vbac034
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