Evidence map›Paper›PMID 20126623›Full record

ArticlePloS one2010

An integrated mass-spectrometry pipeline identifies novel protein coding-regions in the human genome.

Danny A Bitton, Duncan L Smith, Yvonne Connolly, Paul J Scutt, Crispin J Miller

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

19 citing papers in PubMed, 30 citations in OpenAlex.

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  12. Inference and validation of protein identifications.Molecular & cellular proteomics : MCP · 2012
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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

5 authors at 2 institutions in 1 country.

Danny A BittonApplied Computational Biology and Bioinformatics Group, Cancer Research UK, Paterson Institute for Cancer Research, The University of Manchester, Manchester, United Kingdom.
Duncan L Smith
Yvonne Connolly
Paul J Scutt
Crispin J Miller
Cancer Research UK Manchester Institute · GBUniversity of Manchester · GB

Funding

Cancer Research UK
6 · The paper itself

Abstract

backgroundMost protein mass spectrometry (MS) experiments rely on searches against a database of known or predicted proteins, limiting their ability as a gene discovery tool.

resultsUsing a search against an in silico translation of the entire human genome, combined with a series of annotation filters, we identified 346 putative novel peptides [False Discovery Rate (FDR)<5%] in a MS dataset derived from two human breast epithelial cell lines. A subset of these were then successfully validated by a different MS technique. Two of these correspond to novel isoforms of Heterogeneous Ribonuclear Proteins, while the rest correspond to novel loci.

conclusionsMS technology can be used for ab initio gene discovery in human data, which, since it is based on different underlying assumptions, identifies protein-coding genes not found by other techniques. As MS technology continues to evolve, such approaches will become increasingly powerful.

Indexed as

Genome, HumanAmino Acid SequenceAnimalsCell Line, TumorHumansMass SpectrometryMolecular Sequence DataSequence Homology, Amino Acid

Identifiers

PMID20126623
PMCPMC2812506
OpenAlexW2172191247

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.