Daniel J. Nasko

This study improves metagenome-assembled genomes from human gut microbiota using long-read sequencing and novel assembly methods, yielding more high-quality MAGs and uncovering uncultured diversity.

SeqScreen uses ensemble learning to accurately label pathogenic sequences with functional annotations, achieving high recall and precision for microbial pathogenesis.

PASV automates validation and partitioning of protein-coding sequences using conserved residues, achieving high accuracy in classifying RNR, AOX, and PTOX sequences.

The paper examines how RefSeq database growth affects k-mer-based species classification accuracy, finding increased misclassifications and reduced species-level classifications over time.

The paper introduces a method to speed up protein sequence homology searches with minimal loss of sensitivity and specificity by using hierarchical clustering of reference databases.