Evidence map›Paper›PMID 37969874›Full record

ArticleJournal of biomolecular techniques : JBT2023

The Association of Biomolecular Resource Facilities Proteome Informatics Research Group Study on Metaproteomics (iPRG-2020).

Pratik D Jagtap, Michael R Hoopmann, Benjamin A Neely, Antony Harvey, Lukas Käll, Yasset Perez-Riverol, Milky K Abajorga, Julie A Thomas, Susan T Weintraub, Magnus Palmblad

Abstract read
In one paragraph

Article in Journal of biomolecular techniques : JBT, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Pratik D JagtapUniversity of Minnesota MinneapolisMinnesota55455 USA.
Michael R HoopmannInstitute for Systems Biology SeattleWashington98109 USA.
Benjamin A NeelyNational Institute of Standards and Technology CharlestonSouth Carolina29412 USA.
Antony HarveyProtein Metrics LLC ChandlerTexas75758 USA.
Lukas KällRoyal Institute of Technology 114 28Stockholm Sweden.
Yasset Perez-RiverolEuropean Molecular Biology Laboratory European Bioinformatics Institute Wellcome Trust Genome Campus HinxtonCambridgeCB10 1SD United Kingdom.
Milky K AbajorgaUMass Chan Medical School WorcesterMassachusetts01655 USA.
Julie A ThomasRochester Institute of Technology RochesterNew York14623 USA.
Susan T WeintraubUniversity of Texas Health Science Center at San Antonio Texas78229 USA.
Magnus PalmbladCenter for Proteomics and Metabolomics Leiden University Medical Center 2000 RC Leiden The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metaproteomics research using mass spectrometry data has emerged as a powerful strategy to understand the mechanisms underlying microbiome dynamics and the interaction of microbiomes with their immediate environment. Recent advances in sample preparation, data acquisition, and bioinformatics workflows have greatly contributed to progress in this field. In 2020, the Association of Biomolecular Research Facilities Proteome Informatics Research Group launched a collaborative study to assess the bioinformatics options available for metaproteomics research. The study was conducted in 2 phases. In the first phase, participants were provided with mass spectrometry data files and were asked to identify the taxonomic composition and relative taxa abundances in the samples without supplying any protein sequence databases. The most challenging question asked of the participants was to postulate the nature of any biological phenomena that may have taken place in the samples, such as interactions among taxonomic species. In the second phase, participants were provided a protein sequence database composed of the species present in the sample and were asked to answer the same set of questions as for phase 1. In this report, we summarize the data processing methods and tools used by participants, including database searching and software tools used for taxonomic and functional analysis. This study provides insights into the status of metaproteomics bioinformatics in participating laboratories and core facilities.

Indexed as

ProteomeProteomicsComputational BiologyDatabases, ProteinHumansSoftwareProteomebioinformaticsmass spectrometrymetaproteomicsmicrobiometaxonomy

Identifiers

PMID37969874
PMCPMC10644979

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.