SeqEnhDL: sequence-based classification of cell type-specific enhancers using deep learning models.

Journal: BMC research notes
PMID: 33741075

Abstract

OBJECTIVE: To address the challenge of computational identification of cell type-specific regulatory elements on a genome-wide scale.

Authors

  • Yupeng Wang
    BDX Research and Consulting LLC, Herndon, VA, 20171, USA. ywang@bdxconsult.com.
  • Rosario B Jaime-Lara
    Division of Intramural Clinical and Biological Research (DICBR), National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Abhrarup Roy
    Division of Intramural Research, National Institute of Nursing Research, National Institutes of Health, Bethesda, MD, 20892, USA.
  • Ying Sun
    CFAR and I2R, Agency for Science, Technology and Research, Singapore.
  • Xinyue Liu
    BDX Research and Consulting LLC, Herndon, VA, 20171, USA.
  • Paule V Joseph
    Division of Intramural Clinical and Biological Research (DICBR), National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, 20892, USA. paule.joseph@nih.gov.

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