miTAR: a hybrid deep learning-based approach for predicting miRNA targets.

Gu, Tongjun; Zhao, Xiwu; Barbazuk, William Bradley; Lee, Ji-Hyun

Gu, Tongjun; Zhao, Xiwu; Barbazuk, William Bradley; Lee, Ji-Hyun.

Affiliation

Gu T; Bioinformatics, Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, USA. tgu@ufl.edu.
Zhao X; Division of Quantitative Sciences, University of Florida Health Cancer Center, University of Florida, Gainesville, FL, USA. tgu@ufl.edu.
Barbazuk WB; Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.
Lee JH; Bioinformatics, Interdisciplinary Center for Biotechnology Research, University of Florida, Gainesville, FL, USA.

BMC Bioinformatics ; 22(1): 96, 2021 Feb 27.

Article in En | MEDLINE | ID: mdl-33639834

Subject(s)

Deep Learning; MicroRNAs; Humans; MicroRNAs/genetics; Neural Networks, Computer

Key words

Convolutional neural networks; Deep learning; Hybrid model; MiRNA target; Recurrent neural networks

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: MicroRNAs / Deep Learning Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: BMC Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2021 Type: Article Affiliation country: United States

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