Evidence map›Paper›PMID 36318251›Full record

ArticleNucleic acids research2023

SulfAtlas, the sulfatase database: state of the art and new developments.

Mark Stam, Pernelle Lelièvre, Mark Hoebeke, Erwan Corre, Tristan Barbeyron, Gurvan Michel

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
6.4field-weighted citation impact, top 2% 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

45 citing papers in PubMed, 62 citations in OpenAlex.

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  15. Draft genome sequence ofMicrobiology resource announcements · 2025
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  17. Mucinolysome in gut microbiomes of farm animals and humans.bioRxiv : the preprint server for biology · 2025
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  20. Arylsulfamates inhibit colonic Bacteroidota growth through a sulfatase-independent mechanism.Proceedings of the National Academy of Sciences of the United States of America · 2025
    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

6 authors at 1 institution in 1 country.

Mark StamLABGeM, Génomique Métabolique, CEA, Genoscope, Institut François Jacob, CNRS, Université d'Évry, Université Paris-Saclay, 91057, Evry, Ile-de-France, France.
Pernelle LelièvreSorbonne Université, CNRS, Laboratory of Integrative Biology of Marine Models (LBI2M), Station Biologique de Roscoff (SBR), 29680 Roscoff, Bretagne, France.
Mark HoebekeSorbonne Université, CNRS, FR2424, ABiMS, Station Biologique de Roscoff, 29680, Roscoff, Bretagne, France.ORCID 0000-0001-6311-9752
Erwan CorreSorbonne Université, CNRS, FR2424, ABiMS, Station Biologique de Roscoff, 29680, Roscoff, Bretagne, France.
Tristan BarbeyronSorbonne Université, CNRS, Laboratory of Integrative Biology of Marine Models (LBI2M), Station Biologique de Roscoff (SBR), 29680 Roscoff, Bretagne, France.
Gurvan MichelSorbonne Université, CNRS, Laboratory of Integrative Biology of Marine Models (LBI2M), Station Biologique de Roscoff (SBR), 29680 Roscoff, Bretagne, France.ORCID 0000-0002-3009-6205
Centre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SulfAtlas (https://sulfatlas.sb-roscoff.fr/) is a knowledge-based resource dedicated to a sequence-based classification of sulfatases. Currently four sulfatase families exist (S1-S4) and the largest family (S1, formylglycine-dependent sulfatases) is divided into subfamilies by a phylogenetic approach, each subfamily corresponding to either a single characterized specificity (or few specificities in some cases) or to unknown substrates. Sequences are linked to their biochemical and structural information according to an expert scrutiny of the available literature. Database browsing was initially made possible both through a keyword search engine and a specific sequence similarity (BLAST) server. In this article, we will briefly summarize the experimental progresses in the sulfatase field in the last 6 years. To improve and speed up the (sub)family assignment of sulfatases in (meta)genomic data, we have developed a new, freely-accessible search engine using Hidden Markov model (HMM) for each (sub)family. This new tool (SulfAtlas HMM) is also a key part of the internal pipeline used to regularly update the database. SulfAtlas resource has indeed significantly grown since its creation in 2016, from 4550 sequences to 162 430 sequences in August 2022.

Indexed as

SulfatasesDatabases, FactualHumansPhylogenySulfatases

Identifiers

PMID36318251
PMCPMC9825549
OpenAlexW4307846923

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.