Evidence map›Paper›PMID 17517127›Full record

ArticleBMC bioinformatics2007

A computational survey of candidate exonic splicing enhancer motifs in the model plant Arabidopsis thaliana.

Mihaela Pertea, Stephen M Mount, Steven L Salzberg

Abstract readComparative Study
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 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

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.

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3 · Its place in the literature

Who cites it

33 citing papers in PubMed.

  1. No Association between the Plasmodium vivaxAntimicrobial agents and chemotherapy · 2023
    Article
  2. Article
  3. Delayed Protein Changes During Seed Germination.Frontiers in plant science · 2021
    Article
  4. Article
  5. Article
  6. Evolution of Alternative Splicing in Eudicots.Frontiers in plant science · 2019
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
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  14. Identifying splicing regulatory elements with de Bruijn graphs.Journal of computational biology : a journal of computational molecular cell biology · 2014
    Article
  15. Article
  16. Article
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  19. Review
  20. Review
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.

Mihaela PerteaCenter for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. mpertea@umiacs.umd.edu
Stephen M Mount
Steven L Salzberg

Funding

COMPUTATIONAL MODELING OF GENES AND GENE STRUCTURER01LM006845 · NLM · UNIV OF MARYLAND, COLLEGE PARK · PI SALZBERG, STEVEN L. · 1999 to 2010
$5.9M
Bioinformatics Software for Analyzing Microbial GenomesR01LM007938 · NLM · UNIV OF MARYLAND, COLLEGE PARK · PI SALZBERG, STEVEN L. · 2003 to 2006
$757k
NLM NIH HHS R01 LM006845NLM NIH HHS R01 LM007938NLM NIH HHS R01-LM007938
6 · The paper itself

Abstract

backgroundAlgorithmic approaches to splice site prediction have relied mainly on the consensus patterns found at the boundaries between protein coding and non-coding regions. However exonic splicing enhancers have been shown to enhance the utilization of nearby splice sites.

resultsWe have developed a new computational technique to identify significantly conserved motifs involved in splice site regulation. First, 84 putative exonic splicing enhancer hexamers are identified in Arabidopsis thaliana. Then a Gibbs sampling program called ELPH was used to locate conserved motifs represented by these hexamers in exonic regions near splice sites in confirmed genes. Oligomers containing 35 of these motifs have been shown experimentally to induce significant inclusion of A. thaliana exons. Second, integration of our regulatory motifs into two different splice site recognition programs significantly improved the ability of the software to correctly predict splice sites in a large database of confirmed genes. We have released GeneSplicerESE, the improved splice site recognition code, as open source software.

conclusionOur results show that the use of the ESE motifs consistently improves splice site prediction accuracy.

Indexed as

Alternative SplicingArabidopsisComputational BiologyEnhancer Elements, GeneticExonsGenes, PlantRNA, PlantRNA, Plant

Identifiers

PMID17517127
PMCPMC1892810

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LicenceCC BY
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Registered trials

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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.