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PheSom: a term frequency-based method for measuring human phenotype similarity on the basis of MeSH vocabulary.
Liu, Xinhua; Gao, Ling; Peng, Yonglin; Fang, Zhonghai; Wang, Ju.
Afiliação
  • Liu X; Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China.
  • Gao L; School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
  • Peng Y; Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China.
  • Fang Z; Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China.
  • Wang J; School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin, China.
Front Genet ; 14: 1185790, 2023.
Article em En | MEDLINE | ID: mdl-37496714
Background: Phenotype similarity calculation should be used to help improve drug repurposing. In this study, based on the MeSH terms describing the phenotypes deposited in OMIM, we proposed a method, namely, PheSom (Phenotype Similarity On MeSH), to measure the similarity between phenotypes. PheSom counted the number of overlapping MeSH terms between two phenotypes and then took the weight of every MeSH term within each phenotype into account according to the term frequency-inverse document frequency (FIDC). Phenotype-related genes were used for the evaluation of our method. Results: A 7,739 × 7,739 similarity score matrix was finally obtained and the number of phenotype pairs was dramatically decreased with the increase of similarity score. Besides, the overlapping rates of phenotype-related genes were remarkably increased with the increase of similarity score between phenotypes, which supports the reliability of our method. Conclusion: We anticipate our method can be applied to identifying novel therapeutic methods for complex diseases.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Genet Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Genet Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China