AI Medical Compendium Journal:
Microbial genomics

Showing 1 to 7 of 7 articles

Patchy promiscuity: machine learning applied to predict the host specificity of and .

Microbial genomics
and are bacterial species that colonize different animal hosts with sub-types that can cause life-threatening infections in humans. Source attribution of zoonoses is an important goal for infection control as is identification of isolates in reserv...

Using gut microbiome metagenomic hypervariable features for diabetes screening and typing through supervised machine learning.

Microbial genomics
Diabetes mellitus is a complex metabolic disorder and one of the fastest-growing global public health concerns. The gut microbiota is implicated in the pathophysiology of various diseases, including diabetes. This study utilized 16S rRNA metagenomic ...

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...

Deep learning methods in metagenomics: a review.

Microbial genomics
The ever-decreasing cost of sequencing and the growing potential applications of metagenomics have led to an unprecedented surge in data generation. One of the most prevalent applications of metagenomics is the study of microbial environments, such a...

Prediction of prokaryotic transposases from protein features with machine learning approaches.

Microbial genomics
Identification of prokaryotic transposases (Tnps) not only gives insight into the spread of antibiotic resistance and virulence but the process of DNA movement. This study aimed to develop a classifier for predicting Tnps in bacteria and archaea usin...

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...