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Title: AT excursion: A new approach to predict replication origins in viral genomes by locating AT-rich regions
Authors: Chew, D.S.H. 
Leung, M.-Y.
Choi, K.P. 
Issue Date: 21-May-2007
Citation: Chew, D.S.H., Leung, M.-Y., Choi, K.P. (2007-05-21). AT excursion: A new approach to predict replication origins in viral genomes by locating AT-rich regions. BMC Bioinformatics 8 : -. ScholarBank@NUS Repository.
Abstract: Background: Replication origins are considered important sites for understanding the molecular mechanisms involved in DNA replication. Many computational methods have been developed for predicting their locations in archaeal, bacterial and eukaryotic genomes. However, a prediction method designed for a particular kind of genomes might not work well for another. In this paper, we propose the AT excursion method, which is a score-based approach, to quantify local AT abundance in genomic sequences and use the identified high scoring segments for predicting replication origins. This method has the advantages of requiring no preset window size and having rigorous criteria to evaluate statistical significance of high scoring segments. Results: We have evaluated the AT excursion method by checking its predictions against known replication origins in herpesviruses and comparing its performance with an existing base weighted score method (BWS1). Out of 43 known origins, 39 are predicted by either one or the other method and 26 origins are predicted by both. The excursion method identifies six origins not predicted by BWS1, showing that the AT excursion method is a valuable complement to BWS1. We have also applied the AT excursion method to two other families of double stranded DNA viruses, the poxviruses and iridoviruses, of which very few replication origins are documented in the public domain. The prediction results are made available as supplementary materials at 1. Preliminary investigation shows that the proposed method works well on some larger genomes too. Conclusion: The AT excursion method will be a useful computational tool for identifying replication origins in a variety of genomic sequences. © 2007 Chew et al; licensee BioMed Central Ltd.
Source Title: BMC Bioinformatics
ISSN: 14712105
DOI: 10.1186/1471-2105-8-163
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