Nucleosome positioning based on DNA sequence embedding and deep learning.

Han, Guo-Sheng; Li, Qi; Li, Ying

Han, Guo-Sheng; Li, Qi; Li, Ying.

Afiliação

Han GS; Department of Mathematics and Computational Science, Xiangtan University, Xiangtan, 411105, Hunan, China. hangs@xtu.edu.cn.
Li Q; Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering, Xiangtan University, Xiangtan, 411105, Hunan, China. hangs@xtu.edu.cn.
Li Y; Department of Mathematics and Computational Science, Xiangtan University, Xiangtan, 411105, Hunan, China.

BMC Genomics ; 23(Suppl 1): 301, 2022 Apr 13.

Article em En | MEDLINE | ID: mdl-35418074

Assuntos

Aprendizado Profundo; Nucleossomos; Animais; Sequência de Bases; Caenorhabditis elegans/genética; Drosophila melanogaster/genética; Nucleossomos/genética; Extratos Vegetais

Palavras-chave

Bidirectional recurrent neural network; Convolutional neural network; Deep learning; Nucleosome positioning; Word vector

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Nucleossomos / Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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