Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
, 5 (2B), 561-77

Recognition of Cis-Regulatory Elements With Vombat

Affiliations

Recognition of Cis-Regulatory Elements With Vombat

Stefan Posch et al. J Bioinform Comput Biol.

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.

Similar articles

See all similar articles

Cited by 1 article

Publication types

Substances

LinkOut - more resources

Feedback