ArticleBMC bioinformatics2007
AT excursion: a new approach to predict replication origins in viral genomes by locating AT-rich regions.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- MicroRNA Expression Profiling in Canine Myxomatous Mitral Valve Disease Highlights Potential Diagnostic Tool and Molecular Pathways.Veterinary sciences · 2025Article
- Secondary Structure Predictions for Long RNA Sequences Based on Inversion Excursions and MapReduce.IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum : [proceedings]. IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum · 2013Article
- Enhancement of accuracy and efficiency for RNA secondary structure prediction by sequence segmentation and MapReduce.BMC structural biology · 2013Article
- Least-Squares Support Vector Machine Approach to Viral Replication Origin Prediction.INFORMS journal on computing · 2010Article
- De novo search for non-coding RNA genes in the AT-rich genome of Dictyostelium discoideum: performance of Markov-dependent genome feature scoring.Genome research · 2008Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundReplication 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.
resultsWe 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.
conclusionThe AT excursion method will be a useful computational tool for identifying replication origins in a variety of genomic sequences.
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Registered trials
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