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Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm
Over 10,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)‐based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in di...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9305291/ https://www.ncbi.nlm.nih.gov/pubmed/35143083 http://dx.doi.org/10.1002/humu.24341 |
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author | Fujiwara, Toyofumi Shin, Jae‐Moon Yamaguchi, Atsuko |
author_facet | Fujiwara, Toyofumi Shin, Jae‐Moon Yamaguchi, Atsuko |
author_sort | Fujiwara, Toyofumi |
collection | PubMed |
description | Over 10,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)‐based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in diagnosing patients with suspected rare genetic diseases. In September 2017, we released PubCaseFinder (https://pubcasefinder.dbcls.jp), a web‐based CDSS that provides ranked lists of genetic and rare diseases using HPO‐based phenotypic similarities, where top‐listed diseases represent the most likely differential diagnosis. We also developed a Matchmaker Exchange (MME) application programming interface (API) to query PubCaseFinder, which has been adopted by several patient repositories. In this paper, we describe notable updates regarding PubCaseFinder, the GeneYenta matching algorithm implemented in PubCaseFinder, and the PubCaseFinder API. The updated GeneYenta matching algorithm improves the performance of the CDSS automated differential diagnosis function. Moreover, the updated PubCaseFinder and new API empower patient repositories participating in MME and medical professionals to actively use HPO‐based resources. |
format | Online Article Text |
id | pubmed-9305291 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93052912022-07-28 Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm Fujiwara, Toyofumi Shin, Jae‐Moon Yamaguchi, Atsuko Hum Mutat Databases Over 10,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)‐based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in diagnosing patients with suspected rare genetic diseases. In September 2017, we released PubCaseFinder (https://pubcasefinder.dbcls.jp), a web‐based CDSS that provides ranked lists of genetic and rare diseases using HPO‐based phenotypic similarities, where top‐listed diseases represent the most likely differential diagnosis. We also developed a Matchmaker Exchange (MME) application programming interface (API) to query PubCaseFinder, which has been adopted by several patient repositories. In this paper, we describe notable updates regarding PubCaseFinder, the GeneYenta matching algorithm implemented in PubCaseFinder, and the PubCaseFinder API. The updated GeneYenta matching algorithm improves the performance of the CDSS automated differential diagnosis function. Moreover, the updated PubCaseFinder and new API empower patient repositories participating in MME and medical professionals to actively use HPO‐based resources. John Wiley and Sons Inc. 2022-02-22 2022-06 /pmc/articles/PMC9305291/ /pubmed/35143083 http://dx.doi.org/10.1002/humu.24341 Text en © 2022 The Authors. Human Mutation published by Wiley Periodicals LLC https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Databases Fujiwara, Toyofumi Shin, Jae‐Moon Yamaguchi, Atsuko Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm |
title | Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm |
title_full | Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm |
title_fullStr | Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm |
title_full_unstemmed | Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm |
title_short | Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm |
title_sort | advances in the development of pubcasefinder, including the new application programming interface and matching algorithm |
topic | Databases |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9305291/ https://www.ncbi.nlm.nih.gov/pubmed/35143083 http://dx.doi.org/10.1002/humu.24341 |
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