Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model.

Journal: Bioinformatics (Oxford, England)
PMID: 39196755

Abstract

MOTIVATION: 5-Hydroxymethylcytosine (5hmC), a crucial epigenetic mark with a significant role in regulating tissue-specific gene expression, is essential for understanding the dynamic functions of the human genome. Despite its importance, predicting 5hmC modification across the genome remains a challenging task, especially when considering the complex interplay between DNA sequences and various epigenetic factors such as histone modifications and chromatin accessibility.

Authors

  • Xin Ma
    Department of Medical Oncology, Harbin Medical University Cancer Hospital, Harbin, China.
  • Sai Ritesh Thela
    Department of Biostatistics, University of Florida, Gainesville, FL 32603, United States.
  • Fengdi Zhao
    Department of Biostatistics, University of Florida, Gainesville, FL 32603, United States.
  • Bing Yao
    Department of Industrial and Systems Engineering, The University of Tennessee, Knoxville, TN, United States.
  • Zhexing Wen
    Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30322, United States.
  • Peng Jin
  • Jinying Zhao
    Department of Epidemiology, University of Florida, Gainesville, FL 32603, United States.
  • Li Chen
    Department of Endocrinology and Metabolism, Qilu Hospital, Shandong University, Jinan, China.

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