GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization.

Ai, Ning; Liang, Yong; Yuan, Haoliang; Ouyang, Dong; Xie, Shengli; Liu, Xiaoying

Ai, Ning; Liang, Yong; Yuan, Haoliang; Ouyang, Dong; Xie, Shengli; Liu, Xiaoying.

Afiliación

Ai N; Peng Cheng Laboratory, Shenzhen, 518005, Guangdong, China.
Liang Y; School of Computer Science and Engineering, Macau University of Science and Technology, Avenida Wai Long, Taipa, China.
Yuan H; Peng Cheng Laboratory, Shenzhen, 518005, Guangdong, China. yongliangresearch@gmail.com.
Ouyang D; Pazhou Laboratory (Huangpu), Guangzhou, 510555, Guangdong, China. yongliangresearch@gmail.com.
Xie S; School of Automation, Guangdong University of Technology, Guangzhou, 510006, Guangdong, China.
Liu X; Peng Cheng Laboratory, Shenzhen, 518005, Guangdong, China.

BMC Genomics ; 24(1): 424, 2023 Jul 27.

Article en En | MEDLINE | ID: mdl-37501127

Asunto(s)

MicroARNs; ARN Largo no Codificante; Aprendizaje; ARN no Traducido/genética; MicroARNs/genética; ARN Circular; Biología Computacional

Palabras clave

Contrastive learning; Deep graph learning; Deep matrix factorization; Multi-source heterogenous networks; Non-coding RNA-disease associations

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: MicroARNs / ARN Largo no Codificante Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Genomics Asunto de la revista: GENETICA Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo

Imprimir

XML

PubMed Links

Buscar en Google