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Identifying complex motifs in massive omics data with a variable-convolutional layer in deep neural network.
Li, Jing-Yi; Jin, Shen; Tu, Xin-Ming; Ding, Yang; Gao, Ge.
Afiliación
  • Li JY; Biomedical Pioneering Innovation Center & Beijing Advanced Innovation Center for Genomics, Center for Bioinformatics, and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking University, Beijing 100871, China.
  • Jin S; Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
  • Tu XM; Biomedical Pioneering Innovation Center & Beijing Advanced Innovation Center for Genomics, Center for Bioinformatics, and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking University, Beijing 100871, China.
  • Ding Y; Biomedical Pioneering Innovation Center & Beijing Advanced Innovation Center for Genomics, Center for Bioinformatics, and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking University, Beijing 100871, China.
  • Gao G; Biomedical Pioneering Innovation Center & Beijing Advanced Innovation Center for Genomics, Center for Bioinformatics, and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking University, Beijing 100871, China.
Brief Bioinform ; 22(6)2021 11 05.
Article en En | MEDLINE | ID: mdl-34219140
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Redes Neurales de la Computación / Biología Computacional / Secuencias de Aminoácidos / Genómica / Motivos de Nucleótidos / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: China
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Programas Informáticos / Redes Neurales de la Computación / Biología Computacional / Secuencias de Aminoácidos / Genómica / Motivos de Nucleótidos / Aprendizaje Profundo Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: China