ArticleMicrobiologyOpen2026
Integrative Modular, Network-Based, and Machine Learning Framework for Predicting Accessory Genome Functions and Virulence in Escherichia coli O157:H7.
Article in MicrobiologyOpen, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The pathogenicity of Escherichia coli O157:H7 is shaped not only by chromosomal toxins such as Stx and eae but also by virulence and resistance genes carried on plasmids. To explore the modular structure and predictive potential of these accessory elements, presence/absence data from 77 strains (70 accessory features) were analyzed. Methods included clustering using Euclidean and Jaccard distances, gene-to-gene network construction with community detection, Fisher's exact tests for associations between plasmid and virulence or antimicrobial resistance genes (AMR), random forest modeling to predict virulence labels and toxin presence (excluding direct toxin markers), and PCA for visualization. Both clustering approaches revealed broad groupings, though Jaccard clustering better captured co-occurring gene patterns. The co-occurrence network identified 12 modules, including a prominent plasmid-virulence module centered on IncF replicons, stx2, ehxA, toxB, and espP. Fisher's tests showed significant associations, notably between IncFIA and stx2c (p = 5.3 × 10
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.