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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.
Afiliación
  • 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 en 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 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Variación Genética / Proteínas / Bases de Datos Genéticas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Hum Mutat Asunto de la revista: GENETICA MEDICA Año: 2019 Tipo del documento: Article
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Variación Genética / Proteínas / Bases de Datos Genéticas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Hum Mutat Asunto de la revista: GENETICA MEDICA Año: 2019 Tipo del documento: Article