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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...

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Autores principales: Fujiwara, Toyofumi, Shin, Jae‐Moon, Yamaguchi, Atsuko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
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.
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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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