Evidence map›Paper›PMID 18611287›Full record

ArticleBMC research notes2008

Calculation of splicing potential from the Alternative Splicing Mutation Database.

Jason M Bechtel, Preeti Rajesh, Irina Ilikchyan, Ying Deng, Pankaj K Mishra, Qi Wang, Xiaochun Wu, Kirill A Afonin, William E Grose, Ye Wang and 2 more

Abstract read
In one paragraph

Article in BMC research notes, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Alternative Splicing Regulation in Metabolic Disorders.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2025
    Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
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

12 authors.

Jason M BechtelProgram in Bioinformatics and Proteomics/Genomics, University of Toledo Health Science Campus, Toledo, Ohio 43614, USA. jason.bechtel@utoledo.edu
Preeti Rajesh
Irina Ilikchyan
Ying Deng
Pankaj K Mishra
Qi Wang
Xiaochun Wu
Kirill A Afonin
William E Grose
Ye Wang
Sadik Khuder
Alexei Fedorov

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe Alternative Splicing Mutation Database (ASMD) presents a collection of all known mutations inside human exons which affect splicing enhancers and silencers and cause changes in the alternative splicing pattern of the corresponding genes.

findingsAn algorithm was developed to derive a Splicing Potential (SP) table from the ASMD information. This table characterizes the influence of each oligonucleotide on the splicing effectiveness of the exon containing it. If the SP value for an oligonucleotide is positive, it promotes exon retention, while negative SP values mean the sequence favors exon skipping. The merit of the SP approach is the ability to separate splicing signals from a wide range of sequence motifs enriched in exonic sequences that are attributed to protein-coding properties and/or translation efficiency. Due to its direct derivation from observed splice site selection, SP has an advantage over other computational approaches for predicting alternative splicing.

conclusionWe show that a vast majority of known exonic splicing enhancers have highly positive cumulative SP values, while known splicing silencers have core motifs with strongly negative cumulative SP values. Our approach allows for computation of the cumulative SP value of any sequence segment and, thus, gives researchers the ability to measure the possible contribution of any sequence to the pattern of splicing.

Identifiers

PMID18611287
PMCPMC2518266

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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.