Identifying modifications on DNA-bound histones with joint deep learning of multiple binding sites in DNA sequence.

Journal: Bioinformatics (Oxford, England)
PMID: 35809058

Abstract

MOTIVATION: Histone modifications are epigenetic markers that impact gene expression by altering the chromatin structure or recruiting histone modifiers. Their accurate identification is key to unraveling the mechanisms by which they regulate gene expression. However, the solutions for this task can be improved by exploiting multiple relationships from dataset and exploring designs of learning models, for example jointly learning technology.

Authors

  • Yan Li
    Interdisciplinary Research Center for Biology and Chemistry, Liaoning Normal University, Dalian, China.
  • Lijun Quan
    School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
  • Yiting Zhou
    School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
  • Yelu Jiang
    School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
  • Kailong Li
    School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
  • Tingfang Wu
    1 Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China, School of Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, P. R. China.
  • Qiang Lyu
    Department of Computer Science and Technology, Soochow University, Suzhou, Jiangsu, 215006, China.

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