MAGCNSE: predicting lncRNA-disease associations using multi-view attention graph convolutional network and stacking ensemble model.

Liang, Ying; Zhang, Ze-Qun; Liu, Nian-Nian; Wu, Ya-Nan; Gu, Chang-Long; Wang, Ying-Long

Liang, Ying; Zhang, Ze-Qun; Liu, Nian-Nian; Wu, Ya-Nan; Gu, Chang-Long; Wang, Ying-Long.

Afiliação

Liang Y; College of Computer and Information Engineering, Jiangxi Agricultural University, Nanchang, China.
Zhang ZQ; College of Computer and Information Engineering, Jiangxi Agricultural University, Nanchang, China.
Liu NN; College of Computer and Information Engineering, Jiangxi Agricultural University, Nanchang, China.
Wu YN; College of Computer and Information Engineering, Jiangxi Agricultural University, Nanchang, China.
Gu CL; College of Information Science and Engineering, Hunan University, Changsha, China.
Wang YL; College of Computer and Information Engineering, Jiangxi Agricultural University, Nanchang, China. wangyl@jxau.edu.cn.

BMC Bioinformatics ; 23(1): 189, 2022 May 19.

Article em En | MEDLINE | ID: mdl-35590258

Assuntos

RNA Longo não Codificante; Biologia Computacional/métodos; Humanos; Aprendizado de Máquina; Redes Neurais de Computação; RNA Longo não Codificante/genética

Palavras-chave

Attention mechanism; Convolutional neural network; Graph convolutional network; LncRNA-disease associations; Multi-view; Stacking ensemble model

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: RNA Longo não Codificante Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: BMC Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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