ReviewComputational and structural biotechnology journal2021
Computational prediction of secreted proteins in gram-negative bacteria.
Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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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.
The trial behind it
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Who cites it
23 citing papers in PubMed, 41 citations in OpenAlex.
- GeoEPred: A multimodal structure-aware geometric deep learning framework for Gram-negative bacterial secreted effector prediction with sequence semantics.PLoS computational biology · 2026Article
- PLM-effector: unleashing the potential of protein language models for bacterial secreted protein prediction.Briefings in bioinformatics · 2026Article
- MoCETSE: A mixture-of-convolutional experts and transformer-based model for predicting Gram-negative bacterial secreted effectors.PLoS computational biology · 2026Article
- Machine learning for the prediction of gram-negative bacterial secreted effectors: advances and challenges.Frontiers in chemistry · 2026Review
- Transmembrane effector substrates of type IV secretion systems: mechanisms of secretion and insertion into host cell membranes.microLife · 2026Review
- Article
- Genome-wide investigation of outer membrane protein families under mosaic evolution inApplied and environmental microbiology · 2025Article
- Ayu: a machine intelligence tool for identification of extracellular proteins in the marine secretome.Nature communications · 2025Article
- T4SEpp: A pipeline integrating protein language models to predict bacterial type IV secreted effectors.Computational and structural biotechnology journal · 2024Article
- The type II secretion system as an underappreciated and understudied mediator of interbacterial antagonism.Infection and immunity · 2024Review
- The Effects of Codon Usage on Protein Structure and Folding.Annual review of biophysics · 2024Review
- Distribution patterns and influential factors of pathogenic bacteria in freshwater aquaculture sediments.Environmental science and pollution research international · 2024Article
- Protein Sorting Prediction.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Herbivorous Fish Microbiome Adaptations to Sulfated Dietary Polysaccharides.Applied and environmental microbiology · 2023Article
- Bacterial secretion system functions: evidence of interactions and downstream implications.Microbiology (Reading, England) · 2023Article
- DeepSecE: A Deep-Learning-Based Framework for Multiclass Prediction of Secreted Proteins in Gram-Negative Bacteria.Research (Washington, D.C.) · 2023Article
- Article
- Recruitment of heterologous substrates by bacterial secretion systems for transkingdom translocation.Frontiers in cellular and infection microbiology · 2023Review
- Molecular epidemiology and clinical characteristics of the type VI secretion system inFrontiers in microbiology · 2023Article
- Host-microbiome protein-protein interactions capture disease-relevant pathways.Genome biology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gram-negative bacteria harness multiple protein secretion systems and secrete a large proportion of the proteome. Proteins can be exported to periplasmic space, integrated into membrane, transported into extracellular milieu, or translocated into cytoplasm of contacting cells. It is important for accurate, genome-wide annotation of the secreted proteins and their secretion pathways. In this review, we systematically classified the secreted proteins according to the types of secretion systems in Gram-negative bacteria, summarized the known features of these proteins, and reviewed the algorithms and tools for their prediction.
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Registered trials
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.