Evidence map›Paper›PMID 29092937›Full record

ArticleCancer research2017

An Accessible Proteogenomics Informatics Resource for Cancer Researchers.

Matthew C Chambers, Pratik D Jagtap, James E Johnson, Thomas McGowan, Praveen Kumar, Getiria Onsongo, Candace R Guerrero, Harald Barsnes, Marc Vaudel, Lennart Martens and 5 more

Open access · bronzeAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
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

16 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Chasing the Ghost Proteome in the Dark Matter.Molecular & cellular proteomics : MCP · 2025
    Review
  3. Open-Source and FAIR Research Software for Proteomics.Journal of proteome research · 2025
    Review
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  5. Article
  6. 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

15 authors at 1 institution in 1 country.

Matthew C ChambersDepartment of Biochemistry, Vanderbilt University, Nashville, Tennessee.
Pratik D JagtapDepartment of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, Minnesota.
James E JohnsonMinnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota.
Thomas McGowanMinnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota.
Praveen KumarDepartment of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, Minnesota.
Getiria OnsongoMinnesota Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota.
Candace R GuerreroDepartment of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, Minnesota.
Harald BarsnesProteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway.
Marc VaudelKG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.
Lennart MartensVIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.
Björn GrüningDepartment of Computer Science, Albert-Ludwigs-University, Freiburg, Freiburg, Germany.
Ira R CookeComparative Genomics Centre and Department of Molecular and Cell Biology, James Cook University, Queensland, Australia.
Mohammad HeydarianDepartment of Biology, Johns Hopkins University, Baltimore, Maryland.
Karen L ReddyDepartment of Biological Chemistry, Center for Epigenetics and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland.
Timothy J GriffinDepartment of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, Minnesota. tgriffin@umn.edu.
University of Minnesota · US

Funding

Expanding multiplexed kinase biosensor analysis to SWATH-MS (Part 2 of 2)U24CA199347 · NCI · UNIVERSITY OF MINNESOTA · PI GRIFFIN, TIMOTHY J. · 2016 to 2019
$2.4M
NCI NIH HHS U24 CA199347
6 · The paper itself

Abstract

Proteogenomics has emerged as a valuable approach in cancer research, which integrates genomic and transcriptomic data with mass spectrometry-based proteomics data to directly identify expressed, variant protein sequences that may have functional roles in cancer. This approach is computationally intensive, requiring integration of disparate software tools into sophisticated workflows, challenging its adoption by nonexpert, bench scientists. To address this need, we have developed an extensible, Galaxy-based resource aimed at providing more researchers access to, and training in, proteogenomic informatics. Our resource brings together software from several leading research groups to address two foundational aspects of proteogenomics: (i) generation of customized, annotated protein sequence databases from RNA-Seq data; and (ii) accurate matching of tandem mass spectrometry data to putative variants, followed by filtering to confirm their novelty. Directions for accessing software tools and workflows, along with instructional documentation, can be found at z.umn.edu/canresgithub.

Indexed as

SoftwareComputational BiologyGenome, HumanGenomicsHumansNeoplasmsProteomicsTandem Mass SpectrometryTranscriptome

Identifiers

PMID29092937
PMCPMC5675041
OpenAlexW2766678440

What OpenQuestion holds

Textmetadata
LicenceTDM
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.