ArticleScientific reports2017
SecretEPDB: a comprehensive web-based resource for secreted effector proteins of the bacterial types III, IV and VI secretion systems.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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.
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.
Who cites it
27 citing papers in PubMed.
- Hijacked epigenomes: how bacterial effectors rewrite host gene expression.Archives of microbiology · 2026Review
- Machine learning for the prediction of gram-negative bacterial secreted effectors: advances and challenges.Frontiers in chemistry · 2026Review
- Contrastive-learning of language embedding and biological features for cross modality encoding and effector prediction.Nature communications · 2025Article
- From Recognition to Response: Resistance-Effector Gene Interactions in thePlants (Basel, Switzerland) · 2025Review
- T4Seeker: a hybrid model for type IV secretion effectors identification.BMC biology · 2024Article
- Effector Pt9226 fromMicroorganisms · 2024Article
- Genome engineering of disease susceptibility genes for enhancing resistance in plants.Functional & integrative genomics · 2023Review
- TheInternational journal of molecular sciences · 2023Article
- Bacterial secretion system functions: evidence of interactions and downstream implications.Microbiology (Reading, England) · 2023Article
- SecReT6 update: a comprehensive resource of bacterial Type VI Secretion Systems.Science China. Life sciences · 2023Article
- PHI-base in 2022: a multi-species phenotype database for Pathogen-Host Interactions.Nucleic acids research · 2022Article
- BastionHub: a universal platform for integrating and analyzing substrates secreted by Gram-negative bacteria.Nucleic acids research · 2021Article
- DeepT3_4: A Hybrid Deep Neural Network Model for the Distinction Between Bacterial Type III and IV Secreted Effectors.Frontiers in microbiology · 2021Article
- NovelFrontiers in microbiology · 2021Article
- Article
- Domain-centric database to uncover structure of minimally characterized viral genomes.Scientific data · 2020Article
- T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm.Frontiers in microbiology · 2020Article
- Comparative Genomics Reveals Metabolic Specificity ofMicroorganisms · 2019Article
- Stenotrophomonas maltophilia Encodes a VirB/VirD4 Type IV Secretion System That Modulates Apoptosis in Human Cells and Promotes Competition against Heterologous Bacteria, Including Pseudomonas aeruginosa.Infection and immunity · 2019Article
- Bastion3: a two-layer ensemble predictor of type III secreted effectors.Bioinformatics (Oxford, England) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Bacteria translocate effector molecules to host cells through highly evolved secretion systems. By definition, the function of these effector proteins is to manipulate host cell biology and the sequence, structural and functional annotations of these effector proteins will provide a better understanding of how bacterial secretion systems promote bacterial survival and virulence. Here we developed a knowledgebase, termed SecretEPDB (Bacterial Secreted Effector Protein DataBase), for effector proteins of type III secretion system (T3SS), type IV secretion system (T4SS) and type VI secretion system (T6SS). SecretEPDB provides enriched annotations of the aforementioned three classes of effector proteins by manually extracting and integrating structural and functional information from currently available databases and the literature. The database is conservative and strictly curated to ensure that every effector protein entry is supported by experimental evidence that demonstrates it is secreted by a T3SS, T4SS or T6SS. The annotations of effector proteins documented in SecretEPDB are provided in terms of protein characteristics, protein function, protein secondary structure, Pfam domains, metabolic pathway and evolutionary details. It is our hope that this integrated knowledgebase will serve as a useful resource for biological investigation and the generation of new hypotheses for research efforts aimed at bacterial secretion systems.
Indexed as
Identifiers
What OpenQuestion holds
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.