Evidence map›Paper›PMID 24142994›Full record

ArticleMolecular & cellular proteomics : MCP2014

An automated proteogenomic method uses mass spectrometry to reveal novel genes in Zea mays.

Natalie E Castellana, Zhouxin Shen, Yupeng He, Justin W Walley, California Jack Cassidy, Steven P Briggs, Vineet Bafna

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Improving the Genome Annotation ofCurrent genomics · 2021
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  19. PGx: Putting Peptides to BED.Journal of proteome research · 2016
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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

7 authors.

Natalie E CastellanaDepartment of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92092;
Zhouxin Shen
Yupeng He
Justin W Walley
California Jack Cassidy
Steven P Briggs
Vineet Bafna

Funding

TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
CENTER FOR COMPUTATIONAL MASS-SPECTROMETRYP41RR024851 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2008 to 2011
$5.2M
NCRR NIH HHS P41 RR024851NCRR NIH HHS P41 RR24851NIGMS NIH HHS P41 GM103484
6 · The paper itself

Abstract

New technologies in genomics and proteomics have influenced the emergence of proteogenomics, a field at the confluence of genomics, transcriptomics, and proteomics. First generation proteogenomic toolkits employ peptide mass spectrometry to identify novel protein coding regions. We extend first generation proteogenomic tools to achieve greater accuracy and enable the analysis of large, complex genomes. We apply our pipeline to Zea mays, which has a genome comparable in size to human. Our pipeline begins with the comparison of mass spectra to a putative translation of the genome. We select novel peptides, those that match a region of the genome that was not previously known to be protein coding, for grouping into refinement events. We present a novel, probabilistic framework for evaluating the accuracy of each event. Our calculated event probability, or eventProb, considers the number of supporting peptides and spectra, and the quality of each supporting peptide-spectrum match. Our pipeline predicts 165 novel protein-coding genes and proposes updated models for 741 additional genes.

Indexed as

GenomicsProteomicsGenome, PlantHumansMass SpectrometryOpen Reading FramesZea mays

Identifiers

PMID24142994
PMCPMC3879611

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.