Predicting the potential human lncRNA-miRNA interactions based on graph convolution network with conditional random field.

Wang, Wenya; Zhang, Li; Sun, Jianqiang; Zhao, Qi; Shuai, Jianwei

Wang, Wenya; Zhang, Li; Sun, Jianqiang; Zhao, Qi; Shuai, Jianwei.

Afiliación

Wang W; School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, 114051, China.
Zhang L; School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China.
Sun J; School of Automation and Electrical Engineering, Linyi University, Linyi, 276000, China.
Zhao Q; School of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, 114051, China.
Shuai J; Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), and Wenzhou Key Laboratory of Biophysics, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang, 325001, China.

Brief Bioinform ; 23(6)2022 11 19.

Article en En | MEDLINE | ID: mdl-36305458

Asunto(s)

MicroARNs; ARN Largo no Codificante; Humanos; ARN Largo no Codificante/genética; ARN Largo no Codificante/metabolismo; MicroARNs/genética; MicroARNs/metabolismo; Biología Computacional; Algoritmos; Redes Neurales de la Computación

Palabras clave

computational model; conditional random field; graph convolutional network; lncRNAmiRNA interactions; random walk with restart

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: MicroARNs / ARN Largo no Codificante Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Brief Bioinform Asunto de la revista: BIOLOGIA / INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: China

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