Evidence map›Paper›PMID 31732549›Full record

ArticleMolecular & cellular proteomics : MCP2020

Assessing Protein Sequence Database Suitability Using

Richard S Johnson, Brian C Searle, Brook L Nunn, Jason M Gilmore, Molly Phillips, Chris T Amemiya, Michelle Heck, Michael J MacCoss

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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

8 authors.

Richard S JohnsonDepartment of Genome Sciences, University of Washington, Seattle, Washington. Electronic address: rj8@uw.edu.
Brian C SearleInstitute for Systems Biology, Seattle, Washington; Proteome Software, Portland, Oregon.
Brook L NunnDepartment of Genome Sciences, University of Washington, Seattle, Washington.
Jason M GilmoreDepartment of Genome Sciences, University of Washington, Seattle, Washington.
Molly PhillipsDepartment of Biology, University of Washington, Seattle, Washington; School of Natural Sciences, University of California, Merced, California.
Chris T AmemiyaSchool of Natural Sciences, University of California, Merced, California.
Michelle HeckUnited States Department of Agriculture, Agricultural Research Service, Ithaca, New York.
Michael J MacCossDepartment of Genome Sciences, University of Washington, Seattle, Washington.

Funding

TrainingP41GM103533 · NIGMS · UNIVERSITY OF WASHINGTON · PI MACCOSS, MICHAEL · 2012 to 2021
$20.7M
The Chorus Project: A Sustainable Cloud Solution for Mass Spectrometry DataR01GM121696 · NIGMS · UNIVERSITY OF WASHINGTON · PI MACCOSS, MICHAEL · 2017 to 2020
$1.2M
NIGMS NIH HHS P41 GM103533NIGMS NIH HHS R01 GM121696
6 · The paper itself

Abstract

The analysis of samples from unsequenced and/or understudied species as well as samples where the proteome is derived from multiple organisms poses two key questions. The first is whether the proteomic data obtained from an unusual sample type even contains peptide tandem mass spectra. The second question is whether an appropriate protein sequence database is available for proteomic searches. We describe the use of automated

Indexed as

Databases, ProteinAlgorithmsAmino Acid SequenceAnimalsCaenorhabditis elegansHemipteraHumansK562 CellsPeptidesProteinsProteomeProteomicsSequence Analysis, ProteinSkates, FishSoftwareTandem Mass SpectrometryPeptidesProteinsProteomeAlgorithmsCaenorhabditis elegansdata evaluationde novo sequencingmass spectrometrymetaproteomicspeptides*protein identificationquality control and metricssequencing mstandem mass spectrometry

Identifiers

PMID31732549
PMCPMC6944239

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.