ArticleBioinformatics (Oxford, England)2026
Whole-genome prediction of bacterial pathogenic capacity on novel bacteria using protein language models with PathogenFinder2.
Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
- Trial
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- Whole-genome sequence data ofData in brief · 2026Article
- Data of annotated draft genome assemblies of three bacterial isolates from the 'Panchabrihi' rice, soybean, and bean-associated niches in Bangladesh.Data in brief · 2026Article
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- Antimicrobial Resistance and Comparative Genome Analysis of High-RiskMicroorganisms · 2026Article
- First comprehensive whole genome sequencing report of a multidrug-resistantNew microbes and new infections · 2026Article
- Persistence and Environmental Dissemination of a NovelMicroorganisms · 2026Article
- A 'Genome-First' Framework for Next-Generation Bioinputs: From Functional Mining to Rational Synthetic Microbial Communities.Environmental microbiology · 2026Review
- Article
- Draft genome sequence ofMicrobiology resource announcements · 2026Article
- Draft genome sequences of 16 multidrug-resistantMicrobiology resource announcements · 2026Article
- Draft genome sequences of two multidrug-resistantMicrobiology resource announcements · 2026Article
- Review
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
motivationInfectious diseases continue to be a leading cause of mortality and pose a significant global health threat. Thus, the development of tools for surveillance and early detection of emerging pathogens is needed.
resultsWe introduce PathogenFinder2, a novel, alignment-free, taxonomy-agnostic model for predicting bacterial pathogenic capacity in humans using protein language models. It outperforms previous methods, particularly for novel taxa, and provides interpretable outputs by highlighting proteins most relevant to pathogenic potential. These insights aid the identification of virulence factors, vaccine targets, and infection-related metabolic pathways. Furthermore, we introduce the Bacterial Pathogenic Capacity Landscape, which reveals patterns linked to host condition, infection site, microbial antagonism, and environmental origin. AVAILABILITY: The model is freely available online at https://genepi.dk/pathogenfinder2, or as a standalone program (https://github.com/genomicepidemiology/PathogenFinder2).
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