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VIPdb, a genetic Variant Impact Predictor Database.
Hu, Zhiqiang; Yu, Changhua; Furutsuki, Mabel; Andreoletti, Gaia; Ly, Melissa; Hoskins, Roger; Adhikari, Aashish N; Brenner, Steven E.
Afiliação
  • Hu Z; Department of Plant and Microbial Biology, University of California, Berkeley, California.
  • Yu C; Department of Plant and Microbial Biology, University of California, Berkeley, California.
  • Furutsuki M; Department of Bioengineering, University of California, Berkeley, California.
  • Andreoletti G; Department of Plant and Microbial Biology, University of California, Berkeley, California.
  • Ly M; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California.
  • Hoskins R; Department of Plant and Microbial Biology, University of California, Berkeley, California.
  • Adhikari AN; Department of Plant and Microbial Biology, University of California, Berkeley, California.
  • Brenner SE; Division of Data Sciences, University of California, Berkeley, California.
Hum Mutat ; 40(9): 1202-1214, 2019 09.
Article em En | MEDLINE | ID: mdl-31283070
ABSTRACT
Genome sequencing identifies vast number of genetic variants. Predicting these variants' molecular and clinical effects is one of the preeminent challenges in human genetics. Accurate prediction of the impact of genetic variants improves our understanding of how genetic information is conveyed to molecular and cellular functions, and is an essential step towards precision medicine. Over one hundred tools/resources have been developed specifically for this purpose. We summarize these tools as well as their characteristics, in the genetic Variant Impact Predictor Database (VIPdb). This database will help researchers and clinicians explore appropriate tools, and inform the development of improved methods. VIPdb can be browsed and downloaded at https//genomeinterpretation.org/vipdb.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Proteínas / Bases de Dados Genéticas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Variação Genética / Proteínas / Bases de Dados Genéticas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article