Evidence map›Paper›PMID 24533481›Full record

ArticleJournal of proteome research2014

Assessment of MS/MS search algorithms with parent-protein profiling.

Miin S Lin, Justin J Cherny, Claire T Fournier, Samuel J Roth, Danny Krizanc, Michael P Weir

Abstract read
In one paragraph

Article in Journal of proteome research, 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

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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Miin S LinDepartment of Biology and ‡Department of Mathematics and Computer Science, Wesleyan University Middletown Connecticut 06459, United States.
Justin J Cherny
Claire T Fournier
Samuel J Roth
Danny Krizanc
Michael P Weir

Funding

Proteomic Analysis of Translation Initiation in YeastR15GM096228 · NIGMS · WESLEYAN UNIVERSITY · PI WEIR, MICHAEL P · 2011 to 2011
$328k
NIGMS NIH HHS 1R15GM096228NIGMS NIH HHS R15 GM096228
6 · The paper itself

Abstract

Peptide mass spectrometry relies crucially on algorithms that match peptides to spectra. We describe a method to evaluate the accuracy of these algorithms based on the masses of parent proteins before trypsin endoprotease digestion. Measurement of conformance to parent proteins provides a score for comparison of the performances of different algorithms as well as alternative parameter settings for a given algorithm. Tracking of conformance scores for spectrum matches to proteins with progressively lower expression levels revealed that conformance scores are not uniform within data sets but are significantly lower for less abundant proteins. Similarly peptides with lower algorithm peptide-spectrum match scores have lower conformance. Although peptide mass spectrometry data is typically filtered through decoy analysis to ensure a low false discovery rate, this analysis confirms that the filtered data should not be considered as having a uniform confidence. The analysis suggests that use of different algorithms and multiple standardized parameter settings of these algorithms can increase significantly the numbers of peptides identified. This data set can be used as a resource for future algorithm assessment.

Indexed as

AlgorithmsDatabases, ProteinHumansPeptide FragmentsPeptide MappingProteinsProteomicsTandem Mass SpectrometryTrypsinPeptide FragmentsProteinsTrypsin

Identifiers

PMID24533481
PMCPMC3993968

What OpenQuestion holds

Textmetadata
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.