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Bioinformatics Advance Access originally published online on October 26, 2006
Bioinformatics 2006 22(23):2870-2875; doi:10.1093/bioinformatics/btl528
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Published by Oxford University Press 2006
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Adding sequence context to a Markov background model improves the identification of regulatory elements

Nak-Kyeong Kim , Kannan Tharakaraman and John L. Spouge *

National Center for Biotechnology Information, National Library of Medicine National Institutes of Health, Bethesda, MD 20894, USA

*To whom correspondence should be addressed.

Motivation: Many computational methods for identifying regulatory elements use a likelihood ratio between motif and background models. Often, the methods use a background model of independent bases. At least two different Markov background models have been proposed with the aim of increasing the accuracy of predicting regulatory elements. Both Markov background models suffer theoretical drawbacks, so this article develops a third, context-dependent Markov background model from fundamental statistical principles.

Results: Datasets containing known regulatory elements in eukaryotes provided a basis for comparing the predictive accuracies of the different background models. Non-parametric statistical tests indicated that Markov models of order 3 constituted a statistically significant improvement over the background model of independent bases. Our model performed slightly better than the previous Markov background models. We also found that for discriminating between the predictive accuracies of competing background models, the correlation coefficient is a more sensitive measure than the performance coefficient.

Availability: Our C++ program is available at ftp://ftp.ncbi.nih.gov/pub/spouge/papers/archive/AGLAM/2006-07-19

Contact: spouge{at}ncbi.nlm.nih.gov

Supplementary information: Supplementary data are available at Bioinformatics online.

Received on July 24, 2006; revised on September 20, 2006; accepted on October 10, 2006

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