Evidence map›Paper›PMID 27604408›Full record

ArticleHuman mutation2017

ExonImpact: Prioritizing Pathogenic Alternative Splicing Events.

Meng Li, Weixing Feng, Xinjun Zhang, Yuedong Yang, Kejun Wang, Matthew Mort, David N Cooper, Yue Wang, Yaoqi Zhou, Yunlong Liu

Abstract read
In one paragraph

Article in Human mutation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
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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

10 authors.

Meng LiInstitute of Intelligent System and Bioinformatics, College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China.
Weixing FengInstitute of Intelligent System and Bioinformatics, College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China.
Xinjun ZhangCenter for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA.
Yuedong YangInstitute for Glycomics and School of Informatics and Communication Technology, Griffith University, Parklands Dr. Southport QLD 4215, Australia.
Kejun WangInstitute of Intelligent System and Bioinformatics, College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China.
Matthew MortInstitute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK.
David N CooperInstitute of Medical Genetics, Cardiff University, Heath Park, Cardiff CF14 4XN, UK.
Yue WangDepartments of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA.
Yaoqi ZhouInstitute for Glycomics and School of Informatics and Communication Technology, Griffith University, Parklands Dr. Southport QLD 4215, Australia.
Yunlong LiuCenter for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana, 46202, USA.

Funding

Regulation of mRNA splicing by intronic genetic variantsR01CA213466 · NCI · INDIANA UNIVERSITY INDIANAPOLIS · PI LIU, YUNLONG, SKAAR, TODD C. · 2016 to 2018
$1.7M
NCI NIH HHS R01 CA213466
6 · The paper itself

Abstract

Alternative splicing (AS) is a closely regulated process that allows a single gene to encode multiple protein isoforms, thereby contributing to the diversity of the proteome. Dysregulation of the splicing process has been found to be associated with many inherited diseases. However, among the pathogenic AS events, there are numerous "passenger" events whose inclusion or exclusion does not lead to significant changes with respect to protein function. In this study, we evaluate the secondary and tertiary structural features of proteins associated with disease-causing and neutral AS events, and show that several structural features are strongly associated with the pathological impact of exon inclusion. We further develop a machine-learning-based computational model, ExonImpact, for prioritizing and evaluating the functional consequences of hitherto uncharacterized AS events. We evaluated our model using several strategies including cross-validation, and data from the Gene-Tissue Expression (GTEx) and ClinVar databases. ExonImpact is freely available at http://watson.compbio.iupui.edu/ExonImpact.

Indexed as

Alternative SplicingExonsSoftwareAlgorithmsBrainComputational BiologyDatabases, Nucleic AcidGenetic Association StudiesGenetic Predisposition to DiseaseHumansMachine LearningProtein DomainsProtein IsoformsStructure-Activity RelationshipWeb BrowserProtein Isoformsalternative splicingdiseaseexon impactionmachine learning

Identifiers

PMID27604408
PMCPMC5390777

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.