Recognition of cis-regulatory elements with vombat.

Stefan Posch*, Jan Grau, Andre Gohr, Irad Ben-Gal, Alexander E. Kel, Ivo Grosse

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Variable order Markov models and variable order Bayesian trees have been proposed for the recognition of cis-regulatory elements, and it has been demonstrated that they outperform traditional models such as position weight matrices, Markov models, and Bayesian trees for the recognition of binding sites in prokaryotes. Here, we study to which degree variable order models can improve the recognition of eukaryotic cis-regulatory elements. We find that variable order models can improve the recognition of binding sites of all the studied transcription factors. To ease a systematic evaluation of different model combinations based on problem-specific data sets and allow genomic scans of cis-regulatory elements based on fixed and variable order Markov models and Bayesian trees, we provide the VOMBATserver to the public community.

Original languageEnglish
Pages (from-to)561-577
Number of pages17
JournalJournal of Bioinformatics and Computational Biology
Volume5
Issue number2 B
DOIs
StatePublished - Apr 2007
Externally publishedYes

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