Metagenomics involves the study of genetic material obtained directly from communities of
microorganisms living in natural environments. The field of metagenomics has provided …

Graph Neural Networks (GNNs) have emerged as a very powerful and popular machine
learning model for numerous application domains. Each stage of a GNN requires an …

Despite the widespread adoption of k-mer-based methods in bioinformatics, understanding
the influence of k-mer sizes remains a persistent challenge. Selecting an optimal k-mer size …

Diverse communities of organisms inhabit environments ranging from the human digestive
system to marine ecosystems, significantly impacting both human health and the …

The advent of advanced metagenome sequencing techniques has enabled the direct study
of microbial communities in their natural habitats, thereby facilitating the acquisition of …

Metagenomic binning is a crucial step in understanding microbial communities without
culturing. Many unsupervised binning methods follow the two-phase paradigm. In the first …

Metagenomics studies have provided key insights into the composition and structure of
microbial communities found in different environments. Among the techniques used to …

Sparse matrix and tensor computations are challenging to optimize. In contrast to dense
matrix/tensor computations, the pattern of data access is typically irregular for sparse …