Bioinformatics Vol. 17 no. 90001 2001
Pages S199-S206
© 2001 Oxford University Press
Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition
1 Lehrstuhl
für Informatik 5 (Mustererkennung),
Universität
Erlangen-Nürnberg, Martensstr. 3,
D-91058 Erlangen,
2 Department of Molecular and Cell Biology,
University of California at Berkeley, LSA Rm 539, Berkeley, CA
94708, USA
Received on February 5, 2001
; revised on April 2, 2001
; accepted on April 2, 2001
We present an approach to integrate physical properties of DNA, such as DNA bendability or GC content, into our probabilistic promoter recognition system MCPROMOTER. In the new model, a promoter is represented as a sequence of consecutive segments represented by joint likelihoods for DNA sequence and profiles of physical properties. Sequence likelihoods are modeled with interpolated Markov chains, physical properties with Gaussian distributions. The background uses two joint sequence/profile models for coding and non-coding sequences, each consisting of a mixture of a sense and an anti-sense submodel. On a large Drosophila test set, we achieved a reduction of about 30% of false positives when compared with a model solely based on sequence likelihoods.
Contact: Uwe.Ohler{at}informatik.uni-erlangen.de
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