Evidence map›Paper›PMID 37930548›Full record

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

Use of Bastion for the Identification of Secreted Substrates.

Jiawei Wang, Jiahui Li, Christopher J Stubenrauch

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
4.2field-weighted citation impact, top 5% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. ThemicroLife · 2025
    Review
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

3 authors at 3 institutions in 2 countries.

Jiawei WangEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, UK. jwang@ebi.ac.uk.
Jiahui LiInfection Program, Biomedicine Discovery Institute and Department of Microbiology, Monash University, Melbourne, VIC, Australia.
Christopher J StubenrauchInfection Program, Biomedicine Discovery Institute and Department of Microbiology, Monash University, Melbourne, VIC, Australia.
Australian Regenerative Medicine Institute · AUEuropean Bioinformatics Institute · GBMonash University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacteria use secretion systems to translocate numerous proteins into and across cell membranes, but have evolved more specialized secretion systems that can disrupt the normal cellular processes of host cells and compete bacteria or protect the bacteria from host defenses. Among them, Gram-negative bacteria utilize a variety of different proteins secreted by Type 1 to Type 6 secretion systems to transfer substrates into target cells or the surrounding environment, which play key roles in disease and survival. Therefore, these secreted proteins have attracted the attention of a wealth of researchers. The first step to characterizing new substrates of secretion systems is typically identifying candidates bioinformatically, and the Bastion series of substrate predictors provide biologists machine learning tools that can accurately predict these substrates. This chapter will explain how to use the Bastion series for identifying and analyzing secreted substrates in Gram-negative bacteria.

Indexed as

Bacterial Secretion SystemsHealth PersonnelBiological TransportCell MembraneHumansMachine LearningBacterial Secretion SystemsBastionBioinformaticsEffector predictionMachine learningSecretion system

Identifiers

PMID37930548
OpenAlexW4388422641

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.