Evidence map›Paper›PMID 17517140›Full record

ArticleBMC bioinformatics2007

AT excursion: a new approach to predict replication origins in viral genomes by locating AT-rich regions.

David S H Chew, Ming-Ying Leung, Kwok Pui Choi

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. 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 · 2013
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

David S H ChewDepartment of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore. david.chew@nus.edu.sg
Ming-Ying Leung
Kwok Pui Choi
National University of Singapore · SGThe University of Texas at El Paso · US

Funding

TOXICOLOGY PROJECTG12RR008124 · NCRR · UNIVERSITY OF TEXAS EL PASO · PI WALSH, ELIZABETH J · 1992 to 2011
$20.8M
UTSA MBRS SCORE PROGRAMS06GM008194 · NIGMS · UNIVERSITY OF TEXAS SAN ANTONIO · PI TSIN, ANDREW T C · 1989 to 2006
$17.4M
UTEP SCORE InstrumentationS06GM008012 · NIGMS · UNIVERSITY OF TEXAS EL PASO · PI GARZA, KRISTINE M · 1989 to 2010
$15.8M
Undergraduate Biomedical Research Training at UTEPT34GM008048 · NIGMS · UNIVERSITY OF TEXAS EL PASO · PI PANNELL, KEITH H · 1985 to 2020
$9.2M
NCRR NIH HHS 5G12RR008124-11NCRR NIH HHS G12 RR008124NIGMS NIH HHS 3T34GM008048-20S1NIGMS NIH HHS S06 GM008012NIGMS NIH HHS S06 GM008194NIGMS NIH HHS S06GM08012-35NIGMS NIH HHS T34 GM008048
6 · The paper itself

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.

Indexed as

AlgorithmsAT Rich SequenceBase SequenceChromosome MappingGenome, ViralHerpesviridaeMolecular Sequence DataReplication OriginSequence Analysis, DNA

Identifiers

PMID17517140
PMCPMC1904460
OpenAlexW2019360170

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.