Abstract Machine learning is increasingly important in microbiology where it is used for tasks
such as predicting antibiotic resistance and associating human microbiome features with …

Lessons learnt from the COVID-19 pandemic include increased awareness of the potential
for zoonoses and emerging infectious diseases that can adversely affect human health …

Despite advances in sequencing, lack of standardization makes comparisons across studies
challenging and hampers insights into the structure and function of microbial communities …

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has
enabled insights into the ecology and evolution of environmental and host-associated …

Despite recent advances in metagenomic binning, reconstruction of microbial species from
metagenomics data remains challenging. Here we develop variational autoencoders for …

Metagenomics is a new approach to study microorganisms obtained from a specific
environment by functional gene screening or sequencing analysis. Metagenomics studies …

We previously reported on MetaBAT, an automated metagenome binning software tool to
reconstruct single genomes from microbial communities for subsequent analyses of …

Long-read sequencing technologies have substantially improved the assemblies of many
isolate bacterial genomes as compared to fragmented short-read assemblies. However …

Analyzing the microbiome of diverse species and environments using next-generation
sequencing techniques has significantly enhanced our understanding on metabolic …

Functional profiles of microbial communities are typically generated using comprehensive
metagenomic or metatranscriptomic sequence read searches, which are time-consuming …