Theoretical Chemistry Accounts

, Volume 125, Issue 3–6, pp 583–591 | Cite as

PromoterSweep: a tool for identification of transcription factor binding sites

  • Coral del Val
  • Oliver Pelz
  • Karl-Heinz Glatting
  • Endre Barta
  • Agnes Hotz-WagenblattEmail author
Regular Article


There are many tools available for the prediction of potential promoter regions and the transcription factor binding sites (TFBS) harboured by them. Unfortunately, these tools cannot really avoid the prediction of vast amounts of false positives, the greatest problem in promoter analysis. The combination of different methods and algorithms has shown an improvement in prediction accuracy for similar biological problems such as gene prediction. The web-tool presented here uses this approach to perform an exhaustive integrative analysis, identification and annotation of potential promoter regions. The combination of methods employed includes searches in different experimental promoter databases to identify promoter regions and their orthologs, use of TFBS databases and search tools, and a phylogenetic footprinting strategy, combining multiple alignment of genomic sequences together with motif discovery tools that were tested previously in order to get the best method combination. The pipeline is available for academic users at the HUSAR open server It integrates all of this information and identifies among the huge number of TFBS predictions those, which are more likely to be potentially functional.


Promoter Transcription factor Motif discovery Annotation 



Transcription factor binding site


Transcriptional start site




True positive


True negative


False positive


False negative






Correlation coefficient


Extensible markup language


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Copyright information

© Springer-Verlag 2009

Authors and Affiliations

  • Coral del Val
    • 1
    • 2
  • Oliver Pelz
    • 1
  • Karl-Heinz Glatting
    • 1
  • Endre Barta
    • 1
    • 3
    • 4
  • Agnes Hotz-Wagenblatt
    • 1
    Email author
  1. 1.Molecular BiophysicsGerman Cancer Research Center (DKFZ)HeidelbergGermany
  2. 2.Computer Science and Artificial Intelligence, Informatics FacultyUniversity of GranadaGranadaSpain
  3. 3.Agricultural Biotechnology CenterGödöllőHungary
  4. 4.Apoptosis and Genomics Research Group of the Hungarian Academy of Sciences, Research Center for Molecular Medicine, Medical and Health Science CenterUniversity of DebrecenDebrecenHungary

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