Evidence map›Paper›PMID 21840390›Full record

ArticleGenomics2011

The discovery of novel protein-coding features in mouse genome based on mass spectrometry data.

Xiao-Bin Xing, Qing-Run Li, Han Sun, Xing Fu, Fei Zhan, Xiu Huang, Jing Li, Chun-Lei Chen, Yu Shyr, Rong Zeng and 2 more

Open access · greenAbstract read
In one paragraph

Article in Genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

8 citing papers in PubMed, 22 citations in OpenAlex.

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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

12 authors at 4 institutions in 3 countries.

Xiao-Bin XingShanghai Center for Bioinformation Technology, PR China.
Qing-Run Li
Han Sun
Xing Fu
Fei Zhan
Xiu Huang
Jing Li
Chun-Lei Chen
Yu Shyr
Rong Zeng
Yi-Xue Li
Lu Xie
Chinese Academy of Sciences · CNShanghai Center For Bioinformation Technology · CNMRC Laboratory of Molecular Biology · GBShanghai Jiao Tong University · CN

Funding

Barrett's Esophagus Translational Research Network Coordinating CenterU01CA163056 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SHYR, YU · 2011 to 2016
$2.2M
Barrett's Esophagus Translational Research Network Coordinating Center (BETRNetCC)U24CA163056 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SHYR, YU · 2017 to 2022
$2.1M
NCI NIH HHS U01 CA163056NCI NIH HHS U24 CA163056
6 · The paper itself

Abstract

Identifying protein-coding genes in eukaryotic genomes remains a challenge in post-genome era due to the complex gene models. We applied a proteogenomics strategy to detect un-annotated protein-coding regions in mouse genome. High-accuracy tandem mass spectrometry (MS/MS) data from diverse mouse samples were generated by LTQ-Orbitrap mass spectrometer in house. Two searchable diagnostic proteomic datasets were constructed, one with all possible encoding exon junctions, and the other with all putative encoding exons, for the discovery of novel exon splicing events and novel uninterrupted protein-coding regions. Altogether 29,586 unique peptides were identified. Aligning backwards to the mouse genome, the translation of 4471 annotated genes was validated by the known peptides; and 172 genic events were defined in mouse genome by the novel peptides. The approach in the current work can provide substantial evidences for eukaryote genome annotation in encoding genes.

Indexed as

GenomeOpen Reading FramesSoftwareAmino Acid SequenceAnimalsDatabases, ProteinMiceMolecular Sequence DataPeptidesProtein BiosynthesisRNA Splice SitesSequence AlignmentTandem Mass SpectrometryPeptidesRNA Splice Sites

Identifiers

PMID21840390
PMCPMC5757624
OpenAlexW2073432374

What OpenQuestion holds

Textmetadata
LicenceTDM
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.