Your browser doesn't support javascript.
loading
RNABindRPlus: a predictor that combines machine learning and sequence homology-based methods to improve the reliability of predicted RNA-binding residues in proteins.
Walia, Rasna R; Xue, Li C; Wilkins, Katherine; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant.
Afiliación
  • Walia RR; Bioinformatics and Computational Biology Program, Iowa State University, Ames, Iowa, United States of America; Department of Computer Science, Iowa State University, Ames, Iowa, United States of America.
  • Xue LC; College of Information Sciences and Technology, Pennsylvania State University, University Park, Pennsylvania, United States of America.
  • Wilkins K; Department of Plant Pathology and Plant-Microbe Biology, Cornell University, Ithaca, New York, United States of America; Graduate Field of Computational Biology, Cornell University, Ithaca, New York, United States of America.
  • El-Manzalawy Y; Department of Systems and Computer Engineering, Al-Azhar University, Cairo, Egypt.
  • Dobbs D; Bioinformatics and Computational Biology Program, Iowa State University, Ames, Iowa, United States of America; Department of Genetics, Development, and Cell Biology, Iowa State University, Ames, Iowa, United States of America.
  • Honavar V; College of Information Sciences and Technology, Pennsylvania State University, University Park, Pennsylvania, United States of America; Bioinformatics and Genomics Graduate Program, Pennsylvania State University, University Park, Pennsylvania, United States of America; The Huck Institutes of the Lif
PLoS One ; 9(5): e97725, 2014.
Article en En | MEDLINE | ID: mdl-24846307
Asunto(s)
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: Inteligencia Artificial / Proteínas de Unión al ARN / Análisis de Secuencia de ARN / Análisis de Secuencia de Proteína / Modelos Teóricos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos
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: Inteligencia Artificial / Proteínas de Unión al ARN / Análisis de Secuencia de ARN / Análisis de Secuencia de Proteína / Modelos Teóricos Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Animals / Humans Idioma: En Revista: PLoS One Asunto de la revista: CIENCIA / MEDICINA Año: 2014 Tipo del documento: Article País de afiliación: Estados Unidos