Evidence map›Paper›PMID 38995542›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Biodiversity Analysis of Metaproteomics Samples with Unipept: A Comprehensive Tutorial.

Tim Van Den Bossche, Pieter Verschaffelt, Tibo Vande Moortele, Peter Dawyndt, Lennart Martens, Bart Mesuere

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Metaproteomics for Water Biotechnology: Considerations and Study Cases.Advances in experimental medicine and biology · 2026
    Review
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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

6 authors.

Tim Van Den BosscheDepartment of Biomolecular Medicine, Ghent University, Ghent, Belgium.ORCID 0000-0002-5916-2587
Pieter VerschaffeltDepartment of Biomolecular Medicine, Ghent University, Ghent, Belgium.ORCID 0000-0002-6675-1048
Tibo Vande MoorteleDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.ORCID 0000-0002-7813-934X
Peter DawyndtDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.ORCID 0000-0002-1623-9070
Lennart MartensDepartment of Biomolecular Medicine, Ghent University, Ghent, Belgium. unipept@ugent.be.ORCID 0000-0003-4277-658X
Bart MesuereDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.ORCID 0000-0003-0610-3441

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metaproteomics has become a crucial omics technology for studying microbiomes. In this area, the Unipept ecosystem, accessible at https://unipept.ugent.be , has emerged as a valuable resource for analyzing metaproteomic data. It offers in-depth insights into both taxonomic distributions and functional characteristics of complex ecosystems. This tutorial explains essential concepts like Lowest Common Ancestor (LCA) determination and the handling of peptides with missed cleavages. It also provides a detailed, step-by-step guide on using the Unipept Web application and Unipept Desktop for thorough metaproteomics analyses. By integrating theoretical principles with practical methodologies, this tutorial empowers researchers with the essential knowledge and tools needed to fully utilize metaproteomics in their microbiome studies.

Indexed as

BiodiversityMicrobiotaProteomicsSoftwareComputational BiologyHumansMetagenomicsBiodiversityBioinformaticsData analysisMetaproteomicsMicrobiomeProteomicsTutorial

Identifiers

PMID38995542

What OpenQuestion holds

Textmetadata
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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.