Evidence map›Paper›PMID 24263461›Full record

ReviewGenetics in medicine : official journal of the American College of Medical Genetics2014

In silico tools for splicing defect prediction: a survey from the viewpoint of end users.

Xueqiu Jian, Eric Boerwinkle, Xiaoming Liu

Abstract readReview
In one paragraph

Review in Genetics in medicine : official journal of the American College of Medical Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

74 citing papers in PubMed, 145 citations in OpenAlex.

  1. Trial
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  6. Functional Evaluation ofKidney international reports · 2025
    Article
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  8. Observational
  9. Article
  10. Investigation of CFTR Function in Human Nasal Epithelial Cells Informs Personalized Medicine.American journal of respiratory cell and molecular biology · 2024
    Article
  11. Genetic diagnosis of Alport syndrome in 16 Chinese families.Molecular genetics & genomic medicine · 2024
    Article
  12. Article
  13. Characterization of a novelFrontiers in immunology · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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14 more citing papers are in PubMed but not listed here.

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 1 country.

Xueqiu JianDivision of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
Eric Boerwinkle1] Division of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA [2] Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA.
Xiaoming LiuDivision of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA.
The University of Texas Health Science Center at Houston · USBaylor College of Medicine · US

Funding

Building on GWAS for NHLBI-disease: the CHARGE consortiumRC2HL102419 · NHLBI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI BOERWINKLE, ERIC A. · 2009 to 2010
$27.6M
Variable DNA sites predicting interindividual variation in health measuresP50GM065509 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SING, CHARLES · 2001 to 2011
$27.5M
NHLBI NIH HHS RC2 HL102419NHLBI NIH HHS RC2-HL102419NIGMS NIH HHS P50 GM065509NIGMS NIH HHS P50GM065509
6 · The paper itself

Abstract

RNA splicing is the process during which introns are excised and exons are spliced. The precise recognition of splicing signals is critical to this process, and mutations affecting splicing comprise a considerable proportion of genetic disease etiology. Analysis of RNA samples from the patient is the most straightforward and reliable method to detect splicing defects. However, currently, the technical limitation prohibits its use in routine clinical practice. In silico tools that predict potential consequences of splicing mutations may be useful in daily diagnostic activities. In this review, we provide medical geneticists with some basic insights into some of the most popular in silico tools for splicing defect prediction, from the viewpoint of end users. Bioinformaticians in relevant areas who are working on huge data sets may also benefit from this review. Specifically, we focus on those tools whose primary goal is to predict the impact of mutations within the 5' and 3' splicing consensus regions: the algorithms used by different tools as well as their major advantages and disadvantages are briefly introduced; the formats of their input and output are summarized; and the interpretation, evaluation, and prospection are also discussed.

Indexed as

Computer SimulationComputational BiologyGenetic VariationHumansRNA PrecursorsRNA SplicingSoftwareRNA Precursors

Identifiers

PMID24263461
PMCPMC4029872
OpenAlexW1976579581

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.