Abstract

Genome architecture plays a pivotal role in gene regulation. The use of high-throughput methods for chromatin profiling and 3-D interaction mapping provide rich experimental data sets describing genome organization and dynamics. These data challenge development of new models and algorithms connecting genome architecture with epigenetic marks. In this review, we describe how chromatin architecture could be reconstructed from epigenetic data using biophysical or statistical approaches. We discuss the applicability and limitations of these methods for understanding the mechanisms of chromatin organization. We also highlight the emergence of new predictive approaches for scoring effects of structural variations in human cells.

Original languageEnglish
Article number617202
Number of pages15
JournalFrontiers in Genetics
Volume11
DOIs
Publication statusPublished - 22 Jan 2021

Keywords

  • Hi-C
  • machine learning
  • modeling
  • polymer physics
  • predicting approaches

OECD FOS+WOS

  • 1.06.KM GENETICS & HEREDITY

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