Evidence map›Paper›PMID 23142869›Full record

ArticleNature methods2012

De novo derivation of proteomes from transcriptomes for transcript and protein identification.

Vanessa C Evans, Gary Barker, Kate J Heesom, Jun Fan, Conrad Bessant, David A Matthews

Abstract read
In one paragraph

Article in Nature methods, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.

0numbers the graph read from it
0cells of the map it votes in
80citing 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

80 citing papers in PubMed.

  1. Article
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  5. Review
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  11. Proteotranscriptomics - A facilitator in omics research.Computational and structural biotechnology journal · 2022
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
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  20. Article

20 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

6 authors.

Vanessa C EvansSchool of Cellular and Molecular Medicine, University of Bristol, Bristol, UK.
Gary Barker
Kate J Heesom
Jun Fan
Conrad Bessant
David A Matthews

Funding

Biotechnology and Biological Sciences Research Council BB/I00095X/1Biotechnology and Biological Sciences Research Council BB/I001131/1Wellcome Trust 083604
6 · The paper itself

Abstract

Identification of proteins by tandem mass spectrometry requires a reference protein database, but these are only available for model species. Here we demonstrate that, for a non-model species, the sequencing of expressed mRNA can generate a protein database for mass spectrometry-based identification. This combination of high-throughput sequencing and protein identification technologies allows detection of genes and proteins. We use human cells infected with human adenovirus as a complex and dynamic model to demonstrate the robustness of this approach. Our proteomics informed by transcriptomics (PIT) technique identifies >99% of over 3,700 distinct proteins identified using traditional analysis that relies on comprehensive human and adenovirus protein lists. We show that this approach can also be used to highlight genes and proteins undergoing dynamic changes in post-transcriptional protein stability.

Indexed as

TranscriptomeAdenoviridaeAnimalsArginineCarbon IsotopesCHO CellsChromatography, LiquidCricetinaeCricetulusDatabases, ProteinHeLa CellsHumansLysineNitrogen IsotopesNuclear ProteinsPolymorphism, Single NucleotideArginineCarbon IsotopesLysineNitrogen IsotopesNuclear ProteinsPOLDIP3 protein, humanProteomeRNA-Binding ProteinsRNA, Messenger

Identifiers

PMID23142869
PMCPMC3581816

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.