Evidence map›Paper›PMID 20620248›Full record

ReviewJournal of proteomics2010

Proteogenomics to discover the full coding content of genomes: a computational perspective.

Natalie Castellana, Vineet Bafna

Abstract readReview
In one paragraph

Review in Journal of proteomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed
6.9field-weighted citation impact, top 2% 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

68 citing papers in PubMed, 155 citations in OpenAlex.

  1. Article
  2. Article
  3. Metagenomic Assembly and Gene Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  4. Comprehensive Peptide Mapping Is Crucial for Proteogenomics and Proteomics.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  5. Review
  6. Micropeptides translated from putative long non-coding RNAs.Acta biochimica et biophysica Sinica · 2022
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Proteogenomic Analysis ofFrontiers in microbiology · 2018
    Article
  17. Article
  18. Mining for Micropeptides.Trends in cell biology · 2017
    Review
  19. Article
  20. Article

8 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Natalie CastellanaDepartment of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093-0404, USA.
Vineet Bafna
University of California, San Diego · US

Funding

CENTER FOR COMPUTATIONAL MASS-SPECTROMETRYP41RR024851 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2008 to 2011
$5.2M
NCRR NIH HHS 1-P41-RR024851-01NCRR NIH HHS P41 RR024851
6 · The paper itself

Abstract

Proteogenomics has emerged as a field at the junction of genomics and proteomics. It is a loose collection of technologies that allow the search of tandem mass spectra against genomic databases to identify and characterize protein-coding genes. Proteogenomic peptides provide invaluable information for gene annotation, which is difficult or impossible to ascertain using standard annotation methods. Examples include confirmation of translation, reading-frame determination, identification of gene and exon boundaries, evidence for post-translational processing, identification of splice-forms including alternative splicing, and also, prediction of completely novel genes. For proteogenomics to deliver on its promise, however, it must overcome a number of technological hurdles, including speed and accuracy of peptide identification, construction and search of specialized databases, correction of sampling bias, and others. This article reviews the state of the art of the field, focusing on the current successes, and the role of computation in overcoming these challenges. We describe how technological and algorithmic advances have already enabled large-scale proteogenomic studies in many model organisms, including arabidopsis, yeast, fly, and human. We also provide a preview of the field going forward, describing early efforts in tackling the problems of complex gene structures, searching against genomes of related species, and immunoglobulin gene reconstruction.

Indexed as

AnimalsComputational BiologyGenomeHumansOpen Reading FramesProteomeProteomicsProteome

Identifiers

PMID20620248
PMCPMC2949459
OpenAlexW2129148077

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.