A statistical framework for modeling gene expression using chromatin features and application to modENCODE datasets

Genome Biol. 2011;12(2):R15. doi: 10.1186/gb-2011-12-2-r15. Epub 2011 Feb 16.


We develop a statistical framework to study the relationship between chromatin features and gene expression. This can be used to predict gene expression of protein coding genes, as well as microRNAs. We demonstrate the prediction in a variety of contexts, focusing particularly on the modENCODE worm datasets. Moreover, our framework reveals the positional contribution around genes (upstream or downstream) of distinct chromatin features to the overall prediction of expression levels.

MeSH terms

  • Algorithms
  • Animals
  • Caenorhabditis elegans / genetics*
  • Chromatin / genetics*
  • Chromatin / metabolism
  • Cluster Analysis
  • Computational Biology / methods*
  • Data Mining / methods*
  • Gene Expression
  • Gene Expression Profiling*
  • Gene Expression Regulation
  • Histones / genetics*
  • Histones / metabolism
  • Humans
  • MicroRNAs / genetics*
  • MicroRNAs / metabolism
  • Models, Statistical


  • Chromatin
  • Histones
  • MicroRNAs