Evidence map›Paper›PMID 23497682›Full record

ArticleGenome biology2013

DDIG-in: discriminating between disease-associated and neutral non-frameshifting micro-indels.

Huiying Zhao, Yuedong Yang, Hai Lin, Xinjun Zhang, Matthew Mort, David N Cooper, Yunlong Liu, Yaoqi Zhou

Abstract read
In one paragraph

Article in Genome biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

  1. Article
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  5. WGS Revealed NovelInternational journal of molecular sciences · 2023
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  14. Insertions and deletions in the RNA sequence-structure map.Journal of the Royal Society, Interface · 2021
    Article
  15. 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

8 authors.

Huiying Zhao
Yuedong Yang
Hai Lin
Xinjun Zhang
Matthew Mort
David N Cooper
Yunlong Liu
Yaoqi Zhou

Funding

Statistical Energy Functions: a Fragment-based ApproachR01GM085003 · NIGMS · INDIANA UNIVERSITY INDIANAPOLIS · PI ZHOU, YAOQI · 2008 to 2011
$1.1M
NIGMS NIH HHS R01 GM085003NIGMS NIH HHS R01GM085003
6 · The paper itself

Abstract

Micro-indels (insertions or deletions shorter than 21 bps) constitute the second most frequent class of human gene mutation after single nucleotide variants. Despite the relative abundance of non-frameshifting indels, their damaging effect on protein structure and function has gone largely unstudied. We have developed a support vector machine-based method named DDIG-in (Detecting disease-causing genetic variations due to indels) to prioritize non-frameshifting indels by comparing disease-associated mutations with putatively neutral mutations from the 1,000 Genomes Project. The final model gives good discrimination for indels and is robust against annotation errors. A webserver implementing DDIG-in is available at http://sparks-lab.org/ddig.

Indexed as

AlgorithmsConserved SequenceDatabases, GeneticDiseaseDNAFrameshift MutationGene FrequencyHumansINDEL MutationROC CurveSequence Homology, Nucleic AcidSupport Vector MachineDNA

Identifiers

PMID23497682
PMCPMC4053752

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.