EOESGC: predicting miRNA-disease associations based on embedding of embedding and simplified graph convolutional network.

Pang, Shanchen; Zhuang, Yu; Wang, Xinzeng; Wang, Fuyu; Qiao, Sibo

Pang, Shanchen; Zhuang, Yu; Wang, Xinzeng; Wang, Fuyu; Qiao, Sibo.

Afiliación

Pang S; College of Computer Science and Technology, China University of Petroleum, Qingdao, China.
Zhuang Y; College of Computer Science and Technology, China University of Petroleum, Qingdao, China.
Wang X; College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao, China. wangelxz@126.com.
Wang F; College of Computer Science and Technology, China University of Petroleum, Qingdao, China.
Qiao S; College of Computer Science and Technology, China University of Petroleum, Qingdao, China.

BMC Med Inform Decis Mak ; 21(1): 319, 2021 11 16.

Article en En | MEDLINE | ID: mdl-34789236

Asunto(s)

Neoplasias de la Mama; Neoplasias Pulmonares; MicroARNs; Algoritmos; Biología Computacional; Femenino; Humanos; MicroARNs/genética

Palabras clave

Coupled heterogeneous graph; Embedding of embedding; Simplified graph convolutional network; miRNA-disease associations

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / MicroARNs / Neoplasias Pulmonares Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: BMC Med Inform Decis Mak Asunto de la revista: INFORMATICA MEDICA Año: 2021 Tipo del documento: Article País de afiliación: China

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