Machine learning predicts nucleosome binding modes of transcription factors.

Journal: BMC bioinformatics
PMID: 33784978

Abstract

BACKGROUND: Most transcription factors (TFs) compete with nucleosomes to gain access to their cognate binding sites. Recent studies have identified several TF-nucleosome interaction modes including end binding (EB), oriented binding, periodic binding, dyad binding, groove binding, and gyre spanning. However, there are substantial experimental challenges in measuring nucleosome binding modes for thousands of TFs in different species.

Authors

  • K C Kishan
    Golisano College of Computing and Information Sciences, Rochester Institute of Technology, 20 Lomb Memorial Drive, Rochester, NY, 14623, USA.
  • Sridevi K Subramanya
    Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, 1 Lomb Memorial Drive, Rochester, NY, 14623, USA.
  • Rui Li
    Department of Oncology, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, China.
  • Feng Cui
    Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, 84 Lomb Memorial Drive, Rochester, New York, 14623, USA.

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