CORE_TF: a user-friendly interface to identify evolutionary conserved transcription factor binding sites in sets of co-regulated genes

BMC Bioinformatics. 2008 Nov 26;9:495. doi: 10.1186/1471-2105-9-495.


Background: The identification of transcription factor binding sites is difficult since they are only a small number of nucleotides in size, resulting in large numbers of false positives and false negatives in current approaches. Computational methods to reduce false positives are to look for over-representation of transcription factor binding sites in a set of similarly regulated promoters or to look for conservation in orthologous promoter alignments.

Results: We have developed a novel tool, "CORE_TF" (Conserved and Over-REpresented Transcription Factor binding sites) that identifies common transcription factor binding sites in promoters of co-regulated genes. To improve upon existing binding site predictions, the tool searches for position weight matrices from the TRANSFAC R database that are over-represented in an experimental set compared to a random set of promoters and identifies cross-species conservation of the predicted transcription factor binding sites. The algorithm has been evaluated with expression and chromatin-immunoprecipitation on microarray data. We also implement and demonstrate the importance of matching the random set of promoters to the experimental promoters by GC content, which is a unique feature of our tool.

Conclusion: The program CORE_TF is accessible in a user friendly web interface at It provides a table of over-represented transcription factor binding sites in the users input genes' promoters and a graphical view of evolutionary conserved transcription factor binding sites. In our test data sets it successfully predicts target transcription factors and their binding sites.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Artificial Intelligence
  • Base Composition
  • Binding Sites
  • Chromatin Immunoprecipitation
  • Databases, Genetic
  • Evolution, Molecular
  • Gene Expression Regulation*
  • Humans
  • Internet
  • Oligonucleotide Array Sequence Analysis
  • Promoter Regions, Genetic*
  • Sequence Alignment / methods*
  • Software*
  • Transcription Factors / chemistry*
  • Transcription Factors / genetics
  • Transcription Factors / metabolism*
  • User-Computer Interface


  • Transcription Factors