biostudies-literatureUnknown2(1)Gyori BM<h4>Summary</h4>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.<h4>Availability and implementation</h4>The Gilda web service is available at http://grounding.indra.bio with source code, documentation and tutorials available via https://github.com/indralab/gilda.<h4>Supplementary information</h4>Supplementary data are available at <i>Bioinformatics Advances</i> online.Bioinformatics advancesvbac034https://www.ebi.ac.uk/biostudies/studies/S-EPMC9710686biostudies-literatureGilda: biomedical entity text normalization with machine-learned disambiguation as a service.PMC9710686Gyori BMHoyt CTSteppi AfalseGilda: biomedical entity text normalization with machine-learned disambiguation as a service.<h4>Summary</h4>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.<h4>Availability and implementation</h4>The Gilda web service is available at http://grounding.indra.bio with source code, documentation and tutorials available via https://github.com/indralab/gilda.<h4>Supplementary information</h4>Supplementary data are available at <i>Bioinformatics Advances</i> online.2022-01-01T00:00:00Z20222024-11-19T19:27:59.856Z2024-11-19T19:27:59.856ZS-EPMC97106863669936210.1093/bioadv/vbac034