Prediction of biomarker-disease associations based on graph attention network and text representation.

Yang, Minghao; Huang, Zhi-An; Gu, Wenhao; Han, Kun; Pan, Wenying; Yang, Xiao; Zhu, Zexuan

Yang, Minghao; Huang, Zhi-An; Gu, Wenhao; Han, Kun; Pan, Wenying; Yang, Xiao; Zhu, Zexuan.

Afiliação

Yang M; College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518000, China.
Huang ZA; Center for Computer Science and Information Technology, City University of Hong Kong Dongguan Research Institute, Dongguan, China.
Gu W; College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518000, China.
Han K; GeneGenieDx Corp, 160 E Tasman Dr, San Jose, CA 95134.
Pan W; GeneGenieDx Corp, 160 E Tasman Dr, San Jose, CA 95134.
Yang X; GeneGenieDx Corp, 160 E Tasman Dr, San Jose, CA 95134.
Zhu Z; GeneGenieDx Corp, 160 E Tasman Dr, San Jose, CA 95134.

Brief Bioinform ; 23(5)2022 09 20.

Article em En | MEDLINE | ID: mdl-35901464

Assuntos

Biologia Computacional; Software; Biologia Computacional/métodos; Humanos

Palavras-chave

bimodal fusion network; graph attention network; lncRNAdisease associations; miRNAdisease associations; microbedisease associations; text-based relation representation

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Biologia Computacional 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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