Evidence map›Paper›PMID 17189379›Full record

ArticleGenome research2007

Improving gene annotation using peptide mass spectrometry.

Stephen Tanner, Zhouxin Shen, Julio Ng, Liliana Florea, Roderic Guigó, Steven P Briggs, Vineet Bafna

Open access · bronzeAbstract read
In one paragraph

Article in Genome research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 90 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
90citing papers in PubMed, 1 pooled it
–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

90 citing papers in PubMed, 1 synthesis or guideline pooled it, 178 citations in OpenAlex.

  1. Pooled it
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  13. Methods, Tools and Current Perspectives in Proteogenomics.Molecular & cellular proteomics : MCP · 2017
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30 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

7 authors at 3 institutions in 2 countries.

Stephen TannerBioinformatics Program, University of California, San Diego, La Jolla, California 92093-0419, USA. stanner@ucsd.edu
Zhouxin Shen
Julio Ng
Liliana Florea
Roderic Guigó
Steven P Briggs
Vineet Bafna
University of California San Diego · USCentre for Genomic Regulation · ESGeorge Washington University · US

Funding

VISUALIZATION TOOLS FOR AUTOMATED MOLECULAR MICROSCOPYP41RR008605 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PAPADOPOULOS, PHILIP · 1994 to 2011
$28.1M
Computer Mass-SpectrometryR01RR016522 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2002 to 2008
$3.6M
INFRASTRUCTURE OF BIOENGINEERING DEVELOPMENTC06RR017588 · NCRR · UNIVERSITY OF CALIFORNIA SAN DIEGO · PI GOUGH, DAVID A · 2002 to 2002
$696k
NCRR NIH HHS C06 RR017588NCRR NIH HHS P41 RR008605NCRR NIH HHS P41 RR08605NCRR NIH HHS R01 RR016522NCRR NIH HHS RR016522-04A1
6 · The paper itself

Abstract

Annotation of protein-coding genes is a key goal of genome sequencing projects. In spite of tremendous recent advances in computational gene finding, comprehensive annotation remains a challenge. Peptide mass spectrometry is a powerful tool for researching the dynamic proteome and suggests an attractive approach to discover and validate protein-coding genes. We present algorithms to construct and efficiently search spectra against a genomic database, with no prior knowledge of encoded proteins. By searching a corpus of 18.5 million tandem mass spectra (MS/MS) from human proteomic samples, we validate 39,000 exons and 11,000 introns at the level of translation. We present translation-level evidence for novel or extended exons in 16 genes, confirm translation of 224 hypothetical proteins, and discover or confirm over 40 alternative splicing events. Polymorphisms are efficiently encoded in our database, allowing us to observe variant alleles for 308 coding SNPs. Finally, we demonstrate the use of mass spectrometry to improve automated gene prediction, adding 800 correct exons to our predictions using a simple rescoring strategy. Our results demonstrate that proteomic profiling should play a role in any genome sequencing project.

Indexed as

Genetic TechniquesAlgorithmsAlternative SplicingAmino Acid SequenceDatabases, ProteinExonsHumansIntronsMass SpectrometryMolecular Sequence DataPeptidesPolymorphism, Single NucleotideProtein Array AnalysisProteomicsSequence AlignmentPeptides

Identifiers

PMID17189379
PMCPMC1781355
OpenAlexW2122982012

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.