GraphTGI: an attention-based graph embedding model for predicting TF-target gene interactions.

Du, Zhi-Hua; Wu, Yang-Han; Huang, Yu-An; Chen, Jie; Pan, Gui-Qing; Hu, Lun; You, Zhu-Hong; Li, Jian-Qiang

Du, Zhi-Hua; Wu, Yang-Han; Huang, Yu-An; Chen, Jie; Pan, Gui-Qing; Hu, Lun; You, Zhu-Hong; Li, Jian-Qiang.

Afiliación

Du ZH; College of Computer Science and Software Engineering, ShenZhen University, 3688 Nanhai Avenue, Shenzhen, China.
Wu YH; College of Computer Science and Software Engineering, ShenZhen University, 3688 Nanhai Avenue, Shenzhen, China.
Huang YA; College of Computer Science and Software Engineering, ShenZhen University, 3688 Nanhai Avenue, Shenzhen, China.
Chen J; College of Computer Science and Software Engineering, ShenZhen University, 3688 Nanhai Avenue, Shenzhen, China.
Pan GQ; College of Computer Science and Software Engineering, ShenZhen University, 3688 Nanhai Avenue, Shenzhen, China.
Hu L; College of Computer Science and Software Engineering, ShenZhen University, 3688 Nanhai Avenue, Shenzhen, China.
You ZH; School of Computer Science, Northwestern Polytechnical University, Xi'an, China.
Li JQ; College of Computer Science and Software Engineering, ShenZhen University, 3688 Nanhai Avenue, Shenzhen, China.

Brief Bioinform ; 23(3)2022 05 13.

Article en En | MEDLINE | ID: mdl-35511108

Asunto(s)

Redes Neurales de la Computación

Palabras clave

chemical similarity; graph auto-encoder; graph neural network; transcription factor; transcriptional regulatory network

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Redes Neurales de la Computación Tipo de estudio: Prognostic_studies / Risk_factors_studies 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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