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\begin{document}

\title{Advances in the development of PubCaseFinder, including the new
application programming interface and matching algorithm}



\author[1]{Toyofumi  Fujiwara}%
\author[1]{Jae-Moon Shin}%
\author[2]{Atsuko Yamaguchi}%
\affil[1]{Database Center for Life Science}%
\affil[2]{Tokyo City University}%


\vspace{-1em}



  
  \date{June 15, 2024}


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\begin{abstract}
Over 7,000 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.%
\end{abstract}%



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