User profiles for Nicholas Dimonaco
 | Nicholas J. DimonacoMcMaster University | Queen's University Belfast | Aberystwyth University Verified email at mcmaster.ca Cited by 98 |
No one tool to rule them all: prokaryotic gene prediction tool annotations are highly dependent on the organism of study
Motivation The biases in CoDing Sequence (CDS) prediction tools, which have been based
on historic genomic annotations from model organisms, impact our understanding of novel …
on historic genomic annotations from model organisms, impact our understanding of novel …
DeepViral: prediction of novel virus–host interactions from protein sequences and infectious disease phenotypes
Motivation Infectious diseases caused by novel viruses have become a major public health
concern. Rapid identification of virus–host interactions can reveal mechanistic insights into …
concern. Rapid identification of virus–host interactions can reveal mechanistic insights into …
[HTML][HTML] Computational analysis of SARS-CoV-2 and SARS-like coronavirus diversity in human, bat and pangolin populations
In 2019, a novel coronavirus, SARS-CoV-2/nCoV-19, emerged in Wuhan, China, and has
been responsible for the current COVID-19 pandemic. The evolutionary origins of the virus …
been responsible for the current COVID-19 pandemic. The evolutionary origins of the virus …
Accessory genes define species-specific routes to antibiotic resistance
A deeper understanding of the relationship between the antimicrobial resistance (AMR) gene
carriage and phenotype is necessary to develop effective response strategies against this …
carriage and phenotype is necessary to develop effective response strategies against this …
StORF-Reporter: finding genes between genes
Large regions of prokaryotic genomes are currently without any annotation, in part due to
well-established limitations of annotation tools. For example, it is routine for genes using …
well-established limitations of annotation tools. For example, it is routine for genes using …
No one tool to rule them all: Prokaryotic gene prediction tool performance is highly dependent on the organism of study
Motivation The biases in Open Reading Frame (ORF) prediction tools, which have been
based on historic genomic annotations from model organisms, impact our understanding of …
based on historic genomic annotations from model organisms, impact our understanding of …
Accessory genes define species-specific pathways to antibiotic resistance.
Background: The rise of antimicrobial resistance (AMR) is a growing concern globally and a
deeper understanding of AMR gene carriage vs usage is vital for future responses to reduce …
deeper understanding of AMR gene carriage vs usage is vital for future responses to reduce …
DeepViral: infectious disease phenotypes improve prediction of novel virus–host interactions
Motivation Infectious diseases from novel viruses have become a major public health
concern. Rapid identification of virus–host interactions can reveal mechanistic insights into …
concern. Rapid identification of virus–host interactions can reveal mechanistic insights into …
FrameRate: learning the coding potential of unassembled metagenomic reads
Motivation Metagenomic assembly is a slow and computationally intensive process and
despite needing iterative rounds for improvement and completeness the resulting assembly …
despite needing iterative rounds for improvement and completeness the resulting assembly …
O04 Understanding the key role of accessory genes in AMR phenotype through interpretable machine learning techniques
L Dillon, NJ Dimonaco… - JAC-Antimicrobial …, 2023 - academic.oup.com
Background Antimicrobial resistance (AMR) genes are found to be ubiquitous within the
microbiome, even when antimicrobial usage is absent. To identify the AMR phenotype, the most …
microbiome, even when antimicrobial usage is absent. To identify the AMR phenotype, the most …