Evidence map›Paper›PMID 22611296›Full record

ArticleMolecular & cellular proteomics : MCP2012

A mass spectrometry proteomics data management platform.

Vagisha Sharma, Jimmy K Eng, Michael J Maccoss, Michael Riffle

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 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
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  5. Article
  6. Pathways that affect anterior morphogenesis inbioRxiv : the preprint server for biology · 2023
    Article
  7. Article
  8. Article
  9. Review
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  11. Article
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  13. DnaJ Homolog Subfamily B Member 9 Is a Putative Autoantigen in Fibrillary GN.Journal of the American Society of Nephrology : JASN · 2018
    Article
  14. Article
  15. Review
  16. Article
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  20. 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

4 authors.

Vagisha SharmaDepartment of Genome Sciences, University of Washington, Seattle, Washington 98195, USA.
Jimmy K Eng
Michael J Maccoss
Michael Riffle

Funding

ZDS2P REGULATES SWE1P-DEPENDENT POLARIZED CELL GROWTH IN S CEREVISIAEP41RR011823 · NCRR · UNIVERSITY OF WASHINGTON · PI SALVESEN, GUY S. · 1996 to 2011
$24.7M
TrainingP41GM103533 · NIGMS · UNIVERSITY OF WASHINGTON · PI MACCOSS, MICHAEL · 2012 to 2021
$20.7M
NCRR NIH HHS P41 RR011823NCRR NIH HHS P41 RR11823NIGMS NIH HHS P41 GM103533
6 · The paper itself

Abstract

Mass spectrometry-based proteomics is increasingly being used in biomedical research. These experiments typically generate a large volume of highly complex data, and the volume and complexity are only increasing with time. There exist many software pipelines for analyzing these data (each typically with its own file formats), and as technology improves, these file formats change and new formats are developed. Files produced from these myriad software programs may accumulate on hard disks or tape drives over time, with older files being rendered progressively more obsolete and unusable with each successive technical advancement and data format change. Although initiatives exist to standardize the file formats used in proteomics, they do not address the core failings of a file-based data management system: (1) files are typically poorly annotated experimentally, (2) files are "organically" distributed across laboratory file systems in an ad hoc manner, (3) files formats become obsolete, and (4) searching the data and comparing and contrasting results across separate experiments is very inefficient (if possible at all). Here we present a relational database architecture and accompanying web application dubbed Mass Spectrometry Data Platform that is designed to address the failings of the file-based mass spectrometry data management approach. The database is designed such that the output of disparate software pipelines may be imported into a core set of unified tables, with these core tables being extended to support data generated by specific pipelines. Because the data are unified, they may be queried, viewed, and compared across multiple experiments using a common web interface. Mass Spectrometry Data Platform is open source and freely available at http://code.google.com/p/msdapl/.

Indexed as

Database Management SystemsDatabases, ProteinInformation Storage and RetrievalDatabases as TopicElectronic Data ProcessingMass SpectrometryProteomicsSoftware

Identifiers

PMID22611296
PMCPMC3434774

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.