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RECOGNITION OF CIS-REGULATORY ELEMENTS WITH VOMBAT.
- Source :
-
Journal of Bioinformatics & Computational Biology . Apr2007 Special issue b, Vol. 5 Issue 2b, p561-577. 17p. - Publication Year :
- 2007
-
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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 02197200
- Volume :
- 5
- Issue :
- 2b
- Database :
- Academic Search Index
- Journal :
- Journal of Bioinformatics & Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 44279562
- Full Text :
- https://doi.org/10.1142/S0219720007002886