Christopher J. Creevey

Ptolemaea harmonizes antiviral defence system annotations across multiple tools to maximize recovery and resolve discrepancies in bacterial genomes.

The paper evaluates fourteen DNA extraction protocols for microbial DNA from bovine milk and identifies an optimized version of the QIAGEN DNeasy PowerSoil kit as the most effective.

This paper introduces panDecay, a software tool that unifies decay index calculations across different phylogenetic frameworks to assess branch support.

This study uses whole-genome sequencing to characterize multidrug-resistant Escherichia coli from poultry in Nigeria, identifying chromosomal and plasmid-borne resistance genes and virulence factors.

The paper identifies gene co-occurrence patterns in bacterial genomes that reveal fitness trade-offs constraining resistance mechanisms, showing species-specific gene combination rules.

This study characterizes a multidrug-resistant E. coli strain from a sepsis patient using whole-genome sequencing and phenotypic testing, revealing extensive AMR genes and taxonomic ambiguity with related species.

This study analyzes Acidobacteriota genomes to identify plant interaction traits and biogeochemical roles, revealing frequent plant growth-promoting genes and metabolic functions.

The paper integrates microbial abundance time series with fermentation dynamics using mathematical modeling to predict volatile fatty acid production in the rumen.

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.

The paper formalizes and addresses the computational complexity of haplotyping microbial communities using metagenomic data and provides open-source tools for the task.

This paper introduces a method to recover gene haplotypes from metagenomes and shows it accurately identifies mutation rate differences between core and accessory gene families in rumen microbiomes.

This paper introduces a probabilistic method to recover haplotypes from metagenomic data, achieving 100% accuracy in recovering cryptic gene isoforms from HIV-1 strain mix data.

The paper compares mutation calling from whole exome and RNA sequencing data in lactating Holstein cows, finding RNAseq can serve as a proxy for exome sequencing with some limitations.