DeepFormer: a hybrid network based on convolutional neural network and flow-attention mechanism for identifying the function of DNA sequences.

Yao, Zhou; Zhang, Wenjing; Song, Peng; Hu, Yuxue; Liu, Jianxiao

Yao, Zhou; Zhang, Wenjing; Song, Peng; Hu, Yuxue; Liu, Jianxiao.

Affiliation

Yao Z; Key Laboratory of Smart Farming for Agricultural Animals, Huazhong Agricultural University, Wuhan 430070, China.
Zhang W; Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural University, Wuhan 430070, China.
Song P; College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
Hu Y; College of Informatics, Huazhong Agricultural University, Wuhan 430070, China.
Liu J; College of Plant Science & Technology, Huazhong Agricultural University, Wuhan 430070, China.

Brief Bioinform ; 24(2)2023 03 19.

Article in En | MEDLINE | ID: mdl-36917472

Subject(s)

Genomics; Neural Networks, Computer; Base Sequence; Genomics/methods; Chromatin/genetics; Genome

Key words

DNA function prediction; convolutional neural network; flow-attention mechanism; linear attention mechanism; motif

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Neural Networks, Computer / Genomics Type of study: Prognostic_studies Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2023 Type: Article Affiliation country: China

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