Evidence map›Paper›PMID 22535207›Full record

ArticleMolecular & cellular proteomics : MCP2012

A computational tool to detect and avoid redundancy in selected reaction monitoring.

Hannes Röst, Lars Malmström, Ruedi Aebersold

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing 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

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

33 citing papers in PubMed.

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  8. Expanding the Use of Spectral Libraries in Proteomics.Journal of proteome research · 2018
    Review
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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

3 authors.

Hannes RöstDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH 8093, Switzerland.
Lars Malmström
Ruedi Aebersold

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Selected reaction monitoring (SRM), also called multiple reaction monitoring, has become an invaluable tool for targeted quantitative proteomic analyses, but its application can be compromised by nonoptimal selection of transitions. In particular, complex backgrounds may cause ambiguities in SRM measurement results because peptides with interfering transitions similar to those of the target peptide may be present in the sample. Here, we developed a computer program, the SRMCollider, that calculates nonredundant theoretical SRM assays, also known as unique ion signatures (UIS), for a given proteomic background. We show theoretically that UIS of three transitions suffice to conclusively identify 90% of all yeast peptides and 85% of all human peptides. Using predicted retention times, the SRMCollider also simulates time-scheduled SRM acquisition, which reduces the number of interferences to consider and leads to fewer transitions necessary to construct an assay. By integrating experimental fragment ion intensities from large scale proteome synthesis efforts (SRMAtlas) with the information content-based UIS, we combine two orthogonal approaches to create high quality SRM assays ready to be deployed. We provide a user friendly, open source implementation of an algorithm to calculate UIS of any order that can be accessed online at http://www.srmcollider.org to find interfering transitions. Finally, our tool can also simulate the specificity of novel data-independent MS acquisition methods in Q1-Q3 space. This allows us to predict parameters for these methods that deliver a specificity comparable with that of SRM. Using SRM interference information in addition to other sources of information can increase the confidence in an SRM measurement. We expect that the consideration of information content will become a standard step in SRM assay design and analysis, facilitated by the SRMCollider.

Indexed as

SoftwareAmino Acid SequenceComputer SimulationHumansInternetMass SpectrometryMolecular Sequence DataNitrogen IsotopesPeptidesProteomeProteomicsReproducibility of ResultsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsNitrogen IsotopesPeptidesProteomeSaccharomyces cerevisiae Proteins

Identifiers

PMID22535207
PMCPMC3412981

What OpenQuestion holds

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Read underepoch 390

Registered trials

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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.