DAESTB: inferring associations of small molecule-miRNA via a scalable tree boosting model based on deep autoencoder.

Peng, Li; Tu, Yuan; Huang, Li; Li, Yang; Fu, Xiangzheng; Chen, Xiang

Peng, Li; Tu, Yuan; Huang, Li; Li, Yang; Fu, Xiangzheng; Chen, Xiang.

Afiliação

Peng L; College of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China.
Tu Y; Hunan Key Laboratory for Service computing and Novel Software Technology.
Huang L; College of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China.
Li Y; Academy of Arts and Design, Tsinghua University, Beijing, 10084, China.
Fu X; The Future Laboratory, Tsinghua University, Beijing, 10084, China.
Chen X; Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education, Xiangtan University, Xiangtan, 411105, China.

Brief Bioinform ; 23(6)2022 11 19.

Article em En | MEDLINE | ID: mdl-36377749

Assuntos

MicroRNAs; Humanos; Algoritmos; Biologia Computacional/métodos; Predisposição Genética para Doença; MicroRNAs/genética; MicroRNAs/metabolismo; Modelos Biológicos

Palavras-chave

association prediction; deep autoencoder; microRNA; scalable tree boosting; small molecule

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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: MicroRNAs Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Brief Bioinform Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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