Your browser doesn't support javascript.
loading
Integrated unsupervised-supervised modeling and prediction of protein-peptide affinities at structural level.
Zhou, Peng; Wen, Li; Lin, Jing; Mei, Li; Liu, Qian; Shang, Shuyong; Li, Juelin; Shu, Jianping.
Afiliación
  • Zhou P; Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
  • Wen L; Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
  • Lin J; Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
  • Mei L; Institute of Culinary, Sichuan Tourism University, Chengdu 610100, China.
  • Liu Q; Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
  • Shang S; of Ecological Environment Protection, Chengdu Normal University, Chengdu 611130, China.
  • Li J; Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
  • Shu J; Center for Informational Biology, School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
Brief Bioinform ; 23(3)2022 05 13.
Article en En | MEDLINE | ID: mdl-35352094
Asunto(s)
Palabras clave
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Péptidos / Proteínas Tipo de estudio: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: China
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Péptidos / Proteínas Tipo de estudio: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: China