Nicholas J Dimonaco

This study analyzes the genomic diversity of Mycobacterium bovis in Wales using whole-genome sequencing, identifying geographically distinct clusters and SNPs with potential physiological impacts.

GeneFior improves sequence detection by integrating multiple tools and enforcing transparency, reducing false positives while preserving sensitivity to low-abundance variants.

This paper identifies fragilities in gene clustering and pangenome inference methods using PyamilySeq, showing how minor parameters affect results and calling for more transparent methodologies.

This study evaluates the impact of struvite fertiliser on soil antimicrobial resistance and finds no significant increase in AMR genes or resistant bacteria compared to conventional fertilisers.

The paper develops a lineage-specific gene prediction method for metagenomic data, improving protein prediction accuracy and enabling functional analysis of the human gut microbiome.

StORF-Reporter identifies missing genes in prokaryotic genomes by detecting Stop-ORFs in unannotated regions, expanding gene collections across multiple species.

The paper uses machine learning to predict antimicrobial resistance phenotypes from genomic data across 28 bacterial genera, identifying 528 species-specific genomic pathways to resistance.

FrameRate predicts coding frames from unassembled metagenomic reads using machine learning, bypassing assembly and capturing functional profiles efficiently.

The paper evaluates ORF prediction tools and finds their performance varies greatly by organism, with no single tool being most accurate across all genomes.

DeepViral improves prediction of virus-host protein interactions by incorporating disease phenotypes and protein sequences.

The paper compares genomic sequences of SARS-CoV-2, bat-CoV, and pangolin-CoV to identify host-associated divergences and high-impact variants.