Evidence map›Paper›PMID 25362838›Full record

ArticleJournal of bioinformatics and computational biology2014

Identification of best indicators of peptide-spectrum match using a permutation resampling approach.

Malik N Akhtar, Bruce R Southey, Per E Andrén, Jonathan V Sweedler, Sandra L Rodriguez-Zas

Abstract read
In one paragraph

Article in Journal of bioinformatics and computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Malik N AkhtarDepartment of Animal Sciences, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.
Bruce R Southey
Per E Andrén
Jonathan V Sweedler
Sandra L Rodriguez-Zas

Funding

The UIUC Neuroproteomics Center on Cell-Cell SignalingP30DA018310 · NIDA · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI Elena V Romanova · 2004 to 2026
$24.9M
Integration of resources and studies to elucidate neuropeptide signalingR21DA027548 · NIDA · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI RODRIGUEZ ZAS, SANDRA L · 2009 to 2012
$961k
Inflammation-Induced Behavioral Alterations: A Psychogenomic ApproachR21MH096030 · NIMH · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI RODRIGUEZ ZAS, SANDRA L · 2012 to 2013
$430k
NIDA NIH HHS P30 DA018310NIDA NIH HHS R21 DA027548NIMH NIH HHS R21 MH096030
6 · The paper itself

Abstract

Various indicators of observed-theoretical spectrum matches were compared and the resulting statistical significance was characterized using permutation resampling. Novel decoy databases built by resampling the terminal positions of peptide sequences were evaluated to identify the conditions for accurate computation of peptide match significance levels. The methodology was tested on real and manually curated tandem mass spectra from peptides across a wide range of sizes. Spectra match indicators from complementary database search programs were profiled and optimal indicators were identified. The combination of the optimal indicator and permuted decoy databases improved the calculation of the peptide match significance compared to the approaches currently implemented in the database search programs that rely on distributional assumptions. Permutation tests using p-values obtained from software-dependent matching scores and E-values outperformed permutation tests using all other indicators. The higher overlap in matches between the database search programs when using end permutation compared to existing approaches confirmed the superiority of the end permutation method to identify peptides. The combination of effective match indicators and the end permutation method is recommended for accurate detection of peptides.

Indexed as

Amino Acid SequenceAnimalsComputational BiologyDatabases, ProteinMicePeptidesProteomicsSoftwareTandem Mass SpectrometryPeptidesdatabase search programsEnds permuted decoy databaseNeuropeptidespermutationsp-valuesignificance levelstandem MS

Identifiers

PMID25362838
PMCPMC4243829

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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.