Research Themes
Exploring the intersection of computation, microbiology, and global health challenges
Antimicrobial Resistance & One Health
Understanding how AMR develops and spreads across human, animal, and environmental microbiomes using computational and phylogenetic approaches.
Multi-Drug Resistance Evolution & Transmission
Tracking how resistance develops and spreads across the human-animal-environment interface using whole-genome sequencing and phylogenomics.
Microbiome Responses to Antimicrobial Interventions
Investigating the intended and unintended consequences of antimicrobial policies on microbial communities.
Sustainable Food Systems & Agriculture
Developing AI solutions and computational approaches to transform agri-food systems for sustainability and resilience.
AI-Driven Agricultural Innovation
Applying machine learning and large-scale microbiomics to develop intelligent solutions for sustainable food production.
Livestock Production Optimisation
Computational approaches to improve animal health, productivity, and reduce environmental footprint across farming systems.
Rumen Microbiome
Characterising the complex microbial communities of the rumen to understand their role in feed efficiency, animal health, and methane emissions. Using tools such as CowPI and the HoloRuminant framework to integrate metataxonomic and metagenomic data.
Environmental Microbiology & Biotechnology
Exploring bacteriophage applications and methanogen biology to address environmental challenges and climate change.
Phage Therapy & Environmental Management
Harnessing bacteriophages for sustainable environmental biotechnology and novel therapeutic applications against drug-resistant pathogens.
Methanogen Biology & Climate Change
Investigating methane-producing microorganisms to understand and mitigate greenhouse gas emissions from agriculture and the environment.
Phylogenomics
Reconstructing evolutionary histories and inferring relationships across the tree of life using large-scale genomic datasets and novel computational approaches.
Supertree & Supermatrix Methods
Developing and applying methods for combining partially overlapping phylogenetic datasets, including supertree construction and supermatrix concatenation, implemented in tools such as Clann and CatSequences.
Phylogenomic Inference & Adaptive Evolution
Large-scale inference of evolutionary relationships and detection of adaptive evolution across protein-coding genes, using methods implemented in Crann, Clan Check, and Machete.
Methodological Development
Creating novel bioinformatics tools, pipelines, and multi-omics integration approaches for microbiome and genomics research.
Computational Tool Development
Building open-source bioinformatics software for phylogenetic analysis, metagenomics pipelines, machine learning frameworks, and comparative genomics.
Multi-Omics Integration
Developing approaches to integrate metataxonomic, metagenomic, proteomic, and genomic data for comprehensive systems biology insights.
Interdisciplinary by Design
Our research inherently requires collaboration across Computer Science, Microbiology, Clinical Medicine, Agricultural Sciences, and Environmental Engineering. We work within a One Health framework, recognising the interconnectedness of human, animal, and environmental health.
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