Evidence map›Paper›PMID 26629978›Full record

ArticleJournal of proteome research2016

SpectroGene: A Tool for Proteogenomic Annotations Using Top-Down Spectra.

Mikhail Kolmogorov, Xiaowen Liu, Pavel A Pevzner

Abstract read
In one paragraph

Article in Journal of proteome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

3 authors.

Mikhail KolmogorovDepartment of Computer Science and Engineering, UCSD , 9500 Gilman Drive, La Jolla, California, United States.
Xiaowen LiuDepartment of BioHealth Informatics, IUPUI , 719 Indiana Avenue, Suite 304, Indianapolis, Indiana, United States.
Pavel A PevznerDepartment of Computer Science and Engineering, UCSD , 9500 Gilman Drive, La Jolla, California, United States.

Funding

TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
NIGMS NIH HHS 5P41GM103484NIGMS NIH HHS P41 GM103484
6 · The paper itself

Abstract

In the past decade, proteogenomics has emerged as a valuable technique that contributes to the state-of-the-art in genome annotation; however, previous proteogenomic studies were limited to bottom-up mass spectrometry and did not take advantage of top-down approaches. We show that top-down proteogenomics allows one to address the problems that remained beyond the reach of traditional bottom-up proteogenomics. In particular, we show that top-down proteogenomics leads to the discovery of previously unannotated genes even in extensively studied bacterial genomes and present SpectroGene, a software tool for genome annotation using top-down tandem mass spectra. We further show that top-down proteogenomics searches (against the six-frame translation of a genome) identify nearly all proteoforms found in traditional top-down proteomics searches (against the annotated proteome). SpectroGene is freely available at http://github.com/fenderglass/SpectroGene .

Indexed as

Amino Acid SequenceArchaeal ProteinsBacterial ProteinsGenes, ArchaealGenes, BacterialMolecular Sequence AnnotationMolecular Sequence DataProteomeProteomicsPyrococcus furiosusReference StandardsSalmonella typhimuriumArchaeal ProteinsBacterial ProteinsProteomegenome annotationprotein identificationproteogenomicstop-down mass spectrometry

Identifiers

PMID26629978
PMCPMC6020058

What OpenQuestion holds

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Registered trials

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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.