Evaluating metagenomic software is key for optimizing metagenome interpretation and focus
of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI …

Microbiome research has increased dramatically in recent years, driven by advances in
technology and significant reductions in the cost of analysis. Such research has unlocked a …

We propose an efficient framework for genetic subtyping of SARS-CoV-2, the novel coronavirus
that causes the COVID-19 pandemic. Efficient viral subtyping enables visualization and …

Simple Summary Infectious bacteria (microbes) are able to evolve to become resistant to
antibiotics (develop antimicrobial resistance, or AMR). Resistant microbes are harder to treat, …

Advances in high-throughput sequencing have increased the availability of microbiome
sequencing data that can be exploited to characterize microbiome community structure in situ. …

Simple Summary As COVID-19 shifts from pandemic to endemic, emerging variants may be
more or less virulent. Predicting whether an emerging COVID-19 variant has of high risk of …

Recurrent neural networks with memory and attention mechanisms are widely used in
natural language processing because they can capture short and long term sequential …

Analysis of microbiome data involves identifying co-occurring groups of taxa associated with
sample features of interest (eg, disease state). Elucidating such relations is often difficult as …

Background It is a computational challenge for current metagenomic classifiers to keep up
with the pace of training data generated from genome sequencing projects, such as the …

As the COVID-19 pandemic continues, the SARS-CoV-2 virus continues to rapidly mutate
and change in ways that impact virulence, transmissibility, and immune evasion. Genome …