AIMC Topic: Host Specificity

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Predicting Zoonotic Risk of Influenza A Viruses from Host Tropism Protein Signature Using Random Forest.

International journal of molecular sciences
Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortmen...

MOSTPLAS: a self-correction multi-label learning model for plasmid host range prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Plasmids play an essential role in horizontal gene transfer, aiding their host bacteria in acquiring beneficial traits like antibiotic and metal resistance. There exist some plasmids that can transfer, replicate, or persist in multiple or...

Predicting the bacterial host range of plasmid genomes using the language model-based one-class support vector machine algorithm.

Microbial genomics
The prediction of the plasmid host range is crucial for investigating the dissemination of plasmids and the transfer of resistance and virulence genes mediated by plasmids. Several machine learning-based tools have been developed to predict plasmid h...

Large-scale genomic survey with deep learning-based method reveals strain-level phage specificity determinants.

GigaScience
BACKGROUND: Phage therapy, reemerging as a promising approach to counter antimicrobial-resistant infections, relies on a comprehensive understanding of the specificity of individual phages. Yet the significant diversity within phage populations prese...

A guide to machine learning for bacterial host attribution using genome sequence data.

Microbial genomics
With the ever-expanding number of available sequences from bacterial genomes, and the expectation that this data type will be the primary one generated from both diagnostic and research laboratories for the foreseeable future, then there is both an o...