Evidence map›Paper›PMID 38824125›Full record

ArticleScientific data2024

Protein family annotation for the Unified Human Gastrointestinal Proteome by DPCfam clustering.

Federico Barone, Elena Tea Russo, Edith Natalia Villegas Garcia, Marco Punta, Stefano Cozzini, Alessio Ansuini, Alberto Cazzaniga

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. 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

7 authors.

Federico BaroneArea Science Park, Padriciano, 99, 34149, Trieste, Italy.
Elena Tea RussoArea Science Park, Padriciano, 99, 34149, Trieste, Italy.
Edith Natalia Villegas GarciaArea Science Park, Padriciano, 99, 34149, Trieste, Italy.ORCID 0000-0002-7338-2068
Marco PuntaIRCCS San Raffaele Institute, Center for Omics Sciences, Milan, 20132, Italy.
Stefano CozziniArea Science Park, Padriciano, 99, 34149, Trieste, Italy.
Alessio AnsuiniArea Science Park, Padriciano, 99, 34149, Trieste, Italy. alessio.ansuini@areasciencepark.it.
Alberto CazzanigaArea Science Park, Padriciano, 99, 34149, Trieste, Italy. alberto.cazzaniga@areasciencepark.it.ORCID 0000-0001-6271-3303

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Technological advances in massively parallel sequencing have led to an exponential growth in the number of known protein sequences. Much of this growth originates from metagenomic projects producing new sequences from environmental and clinical samples. The Unified Human Gastrointestinal Proteome (UHGP) catalogue is one of the most relevant metagenomic datasets with applications ranging from medicine to biology. However, the low levels of sequence annotation may impair its usability. This work aims to produce a family classification of UHGP sequences to facilitate downstream structural and functional annotation. This is achieved through the release of the DPCfam-UHGP50 dataset containing 10,778 putative protein families generated using DPCfam clustering, an unsupervised pipeline grouping sequences into single or multi-domain architectures. DPCfam-UHGP50 considerably improves family coverage at protein and residue levels compared to the manually curated repository Pfam. In the hope that DPCfam-UHGP50 will foster future discoveries in the field of metagenomics of the human gut, we release a FAIR-compliant database of our results that is easily accessible via a searchable web server and Zenodo repository.

Indexed as

ProteomeCluster AnalysisDatabases, ProteinGastrointestinal TractHumansMetagenomicsMolecular Sequence AnnotationProteome

Identifiers

PMID38824125
PMCPMC11144186

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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.