Evidence map›Paper›PMID 26670565›Full record

ReviewMass spectrometry reviews2017

Proteogenomics from a bioinformatics angle: A growing field.

Gerben Menschaert, David Fenyö

Abstract readReview
In one paragraph

Review in Mass spectrometry reviews, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. PepCentric Enables Fast Repository-Scale Proteogenomics Searches.bioRxiv : the preprint server for biology · 2025
    Article
  5. Article
  6. Article
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  8. From Gene to Whole Cell: Modeling, Visualization, and Analysis.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
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  17. Article
  18. Article
  19. Review
  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

2 authors.

Gerben MenschaertDepartment of Mathematical Modeling, Statistics and Bioinformatics, Faculty of Bioscience Engineering, Lab of Bioinformatics and Computational Genomics, Ghent University, Ghent, Belgium.
David FenyöDepartment of Biochemistry and Molecular Pharmacology, Center for Health Informatics and Bioinformatics, New York University School of Medicine, New York, NY.

Funding

Cancer Proteome Center at Washington Univ, Univ of North Carolina & Boise StateU24CA160035 · NCI · WASHINGTON UNIVERSITY · PI CHEN, XIAN, ELLIS, MATTHEW J · 2011 to 2016
$11.8M
Proteogenomic Data Analysis for Cancer Systems Biology and Clinical TranslationU24CA210972 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DING, LI, FENYO, DAVID · 2016 to 2020
$3.3M
NCI NIH HHS U24 CA160035NCI NIH HHS U24 CA210972
6 · The paper itself

Abstract

Proteogenomics is a research area that combines areas as proteomics and genomics in a multi-omics setup using both mass spectrometry and high-throughput sequencing technologies. Currently, the main goals of the field are to aid genome annotation or to unravel the proteome complexity. Mass spectrometry based identifications of matching or homologues peptides can further refine gene models. Also, the identification of novel proteoforms is also made possible based on detection of novel translation initiation sites (cognate or near-cognate), novel transcript isoforms, sequence variation or novel (small) open reading frames in intergenic or un-translated genic regions by analyzing high-throughput sequencing data from RNAseq or ribosome profiling experiments. Other proteogenomics studies using a combination of proteomics and genomics techniques focus on antibody sequencing, the identification of immunogenic peptides or venom peptides. Over the years, a growing amount of bioinformatics tools and databases became available to help streamlining these cross-omics studies. Some of these solutions only help in specific steps of the proteogenomics studies, e.g. building custom sequence databases (based on next generation sequencing output) for mass spectrometry fragmentation spectrum matching. Over the last few years a handful integrative tools also became available that can execute complete proteogenomics analyses. Some of these are presented as stand-alone solutions, whereas others are implemented in a web-based framework such as Galaxy. In this review we aimed at sketching a comprehensive overview of all the bioinformatics solutions that are available for this growing research area. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:584-599, 2017.

Indexed as

Databases, FactualAnimalsAntibodiesComputational BiologyGenomicsMass SpectrometryPeptide MappingPeptidesProteomicsSequence Analysis, ProteinSoftwareVenomsAntibodiesPeptidesVenomsbioinformaticsgene annotationmass spectrometrynext-generation sequencingproteoformproteogenomicsribosome profiling

Identifiers

PMID26670565
PMCPMC6101030

What OpenQuestion holds

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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.