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NAR
2006

VOMBAT: prediction of transcription factor binding sites using variable order Bayesian trees

13 years 3 months ago
VOMBAT: prediction of transcription factor binding sites using variable order Bayesian trees
Variable order Markov models and variable order Bayesian trees have been proposed for the recognition of transcription factor binding sites, and it could be demonstrated that they outperform traditional models, such as position weight matrices, Markov models and Bayesian trees. We develop a web server for the recognition of DNA binding sites based on variable order Markov models and variable order Bayesian trees offering the following functionality: (i) given datasets with annotated binding sites and genomic background sequences, variable order Markov models and variable order Bayesian trees can be trained; (ii) given a set of trained models, putative DNA binding sites can be predicted in a given set of genomic sequences and (iii) given a dataset with annotated binding sites and a dataset with genomic background sequences, cross-validation experiments for different model combinations with different parameter settings can be performed. Several of the offered services are computationall...
Jan Grau, Irad E. Ben-Gal, Stefan Posch, Ivo Gross
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2006
Where NAR
Authors Jan Grau, Irad E. Ben-Gal, Stefan Posch, Ivo Grosse
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