ArticleNucleic acids research2021
Peryton: a manual collection of experimentally supported microbe-disease associations.
Article in Nucleic acids research, 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
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
23 citing papers in PubMed.
- Article
- The Role of Gut Microbiota and Mucin Barrier in the Pathogenesis of Colorectal Cancer.Current issues in molecular biology · 2025Review
- Multi-scale information fusion and decoupled representation learning for robust microbe-disease interaction prediction.Journal of pharmaceutical analysis · 2025Article
- Article
- BGMDB: A curated database linking gut microbiota dysbiosis to brain disorders.Computational and structural biotechnology journal · 2025Article
- An Explainable Graph Neural Framework to Identify Cancer-Associated Intratumoral Microbial Communities.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Predicting disease-associated microbes based on similarity fusion and deep learning.Briefings in bioinformatics · 2024Article
- The role of KLF5 in gut microbiota and lung adenocarcinoma: unveiling programmed cell death pathways and prognostic biomarkers.Discover oncology · 2024Article
- Identification of microbe-disease signed associations via multi-scale variational graph autoencoder based on signed message propagation.BMC biology · 2024Article
- Analysis of Human Milk Microbiota in Northern Greece by Comparative 16S rRNA Sequencing vs. Local Dairy Animals.Nutrients · 2024Article
- Article
- Predicting microbe-disease association based on graph autoencoder and inductive matrix completion with multi-similarities fusion.Frontiers in microbiology · 2024Article
- A computational model for potential microbe-disease association detection based on improved graph convolutional networks and multi-channel autoencoders.Frontiers in microbiology · 2024Article
- Identifying disease-related microbes based on multi-scale variational graph autoencoder embedding Wasserstein distance.BMC biology · 2023Article
- Predicting potential microbe-disease associations based on auto-encoder and graph convolution network.BMC bioinformatics · 2023Article
- GMMAD: a comprehensive database of human gut microbial metabolite associations with diseases.BMC genomics · 2023Article
- Achieving pan-microbiome biological insights via the dbBact knowledge base.Nucleic acids research · 2023Article
- In-silico computational approaches to study microbiota impacts on diseases and pharmacotherapy.Gut pathogens · 2023Review
- MNNMDA: Predicting human microbe-disease association via a method to minimize matrix nuclear norm.Computational and structural biotechnology journal · 2023Article
- AGAMEMNON: an Accurate metaGenomics And MEtatranscriptoMics quaNtificatiON analysis suite.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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present Peryton (https://dianalab.e-ce.uth.gr/peryton/), a database of experimentally supported microbe-disease associations. Its first version constitutes a novel resource hosting more than 7900 entries linking 43 diseases with 1396 microorganisms. Peryton's content is exclusively sustained by manual curation of biomedical articles. Diseases and microorganisms are provided in a systematic, standardized manner using reference resources to create database dictionaries. Information about the experimental design, study cohorts and the applied high- or low-throughput techniques is meticulously annotated and catered to users. Several functionalities are provided to enhance user experience and enable ingenious use of Peryton. One or more microorganisms and/or diseases can be queried at the same time. Advanced filtering options and direct text-based filtering of results enable refinement of returned information and the conducting of tailored queries suitable to different research questions. Peryton also provides interactive visualizations to effectively capture different aspects of its content and results can be directly downloaded for local storage and downstream analyses. Peryton will serve as a valuable source, enabling scientists of microbe-related disease fields to form novel hypotheses but, equally importantly, to assist in cross-validation of findings.
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.