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HCRNet: high-throughput circRNA-binding event identification from CLIP-seq data using deep temporal convolutional network.
Yang, Yuning; Hou, Zilong; Wang, Yansong; Ma, Hongli; Sun, Pingping; Ma, Zhiqiang; Wong, Ka-Chun; Li, Xiangtao.
Affiliation
  • Yang Y; School of Information Science and Technology, Northeast Normal University, Changchun, Jilin, China.
  • Hou Z; School of Artificial Intelligence, Jilin University, Changchun, Jilin, China.
  • Wang Y; School of Artificial Intelligence, Jilin University, Changchun, Jilin, China.
  • Ma H; School of Mathematics, Shandong University, Jinan, Shandong, China.
  • Sun P; School of Information Science and Technology, Northeast Normal University, Changchun, Jilin, China.
  • Ma Z; School of Information Science and Technology, Northeast Normal University, Changchun, Jilin, China.
  • Wong KC; School of Computer Science, City University of Hong Kong, Hong Kong SAR.
  • Li X; School of Artificial Intelligence, Jilin University, Changchun, Jilin, China.
Brief Bioinform ; 23(2)2022 03 10.
Article in En | MEDLINE | ID: mdl-35189638
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Full text: 1 Database: MEDLINE Main subject: Chromatin Immunoprecipitation Sequencing / RNA, Circular Type of study: Diagnostic_studies Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2022 Type: Article Affiliation country: China
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Full text: 1 Database: MEDLINE Main subject: Chromatin Immunoprecipitation Sequencing / RNA, Circular Type of study: Diagnostic_studies Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2022 Type: Article Affiliation country: China