AI Medical Compendium Journal:
mBio

Showing 1 to 10 of 10 articles

Machine learning reveals the dynamic importance of accessory sequences for outbreak clustering.

mBio
UNLABELLED: Bacterial typing at whole-genome scales is now feasible owing to decreasing costs in high-throughput sequencing and the recent advances in computation. The unprecedented resolution of whole-genome typing is achieved by genotyping the vari...

Improving viral annotation with artificial intelligence.

mBio
Viruses of bacteria, "phages," are fundamental, poorly understood components of microbial community structure and function. Additionally, their dependence on hosts for replication positions phages as unique sensors of ecosystem features and environme...

Nine (not so simple) steps: a practical guide to using machine learning in microbial ecology.

mBio
Due to the complex nature of microbiome data, the field of microbial ecology has many current and potential uses for machine learning (ML) modeling. With the increased use of predictive ML models across many disciplines, including microbial ecology, ...

Preclinical efficacy of a cell division protein candidate gonococcal vaccine identified by artificial intelligence.

mBio
Vaccines to curb the global spread of multidrug-resistant gonorrhea are urgently needed. Here, 26 vaccine candidates identified by an artificial intelligence-driven platform (Efficacy Discriminative Educated Network[EDEN]) were screened for efficacy ...

Combination of deep XLMS with deep learning reveals an ordered rearrangement and assembly of a major protein component of the vaccinia virion.

mBio
An outstanding problem in the understanding of poxvirus biology is the molecular structure of the mature virion. Via deep learning methods combined with chemical cross-linking mass spectrometry, we have addressed the structure and assembly pathway of...

A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates.

mBio
Variation in the genome of , an important pathogen, can have dramatic impacts on the bacterium's ability to cause disease. We therefore asked whether it was possible to predict the virulence of isolates based on their genomic content. We applied a m...

A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems.

mBio
Machine learning (ML) modeling of the human microbiome has the potential to identify microbial biomarkers and aid in the diagnosis of many diseases such as inflammatory bowel disease, diabetes, and colorectal cancer. Progress has been made toward dev...

Gene Essentiality Analyzed by Transposon Mutagenesis and Machine Learning in a Stable Haploid Isolate of .

mBio
Knowing the full set of essential genes for a given organism provides important information about ways to promote, and to limit, its growth and survival. For many non-model organisms, the lack of a stable haploid state and low transformation efficien...

IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

mBio
UNLABELLED: In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In...