Inferring combinatorial regulation of transcription in silico

Nucleic Acids Res. 2005 Jan 12;33(1):272-9. doi: 10.1093/nar/gki167. Print 2005.


In this paper, we propose a functional view on the in silico prediction of transcriptional regulation. We present a method to predict biological functions regulated by a combinatorial interaction of transcription factors. Using a rigorous statistic, this approach intersects the presence of transcription factor binding sites in gene upstream sequences with Gene Ontology terms associated with these genes. We demonstrate that for the well-studied set of skeletal muscle-related transcription factors Myf-2, Mef and TEF, the correct functions are predicted. Furthermore, starting from the well-characterized promoter of a gene expressed upon lipopolysaccharide stimulation, we predict functional targets of this stimulus. These results are in excellent agreement with microarray data.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Binding Sites
  • Computational Biology / methods*
  • Gene Expression Profiling
  • Gene Expression Regulation*
  • Genomics / methods*
  • Humans
  • Lipopolysaccharides / pharmacology
  • Muscle, Skeletal / metabolism
  • Myogenic Regulatory Factors / metabolism
  • Software
  • Transcription Factors / metabolism*
  • Transcriptional Activation


  • Lipopolysaccharides
  • Myogenic Regulatory Factors
  • Transcription Factors