We are a computational biology group working on microbial communities — developing machine learning/AI and bioinformatics tools to explore metagenomic data, AMR, ruminant biology, food systems, and environmental change.
We're applying machine learning and deep learning to genomic and metagenomic data — from predicting antimicrobial resistance and optimizing sustainable agriculture, to understanding complex microbial ecosystems and driving environmental biotechnology.
Five interconnected areas, each drawing on machine learning and bioinformatics to ask how microbes work — and why it matters.
Understanding how AMR develops and spreads across human, animal, and environmental microbiomes using machine learning, computational, and phylogenetic approaches.
Developing AI solutions and computational approaches to transform agri-food systems for sustainability and resilience.
Exploring bacteriophage applications and methanogen biology to address environmental challenges and climate change.
Reconstructing evolutionary histories and inferring relationships across the tree of life using large-scale genomic datasets and novel computational approaches.
Creating novel machine learning frameworks, bioinformatics tools, pipelines, and multi-omics integration approaches for microbiome and genomics research.
An interdisciplinary group of computational biologists, machine learning researchers, bioinformaticians, and microbiologists based at the Institute for Global Food Security, Queen's University Belfast.
We write open-source bioinformatics and machine learning tools — here's a sample.
A computational pipeline for identifying novel Antimicrobial Peptides (AMPs) from any form of digital biological data, for synthesis and screening against multi-drug resistant bacteria and fungi.
A tool for easy implementation of j48 decision trees from WEKA on novel datasets, developed to streamline machine learning workflows in bioinformatics.
Automated Quality Improvement for multiple sequence alignments. Automatically identifies the most reliable alignment for a given protein family using MUSCLE, MAFFT, RASCAL, and NORMD.
A tool for concatenating multiple FASTA alignments for supermatrix phylogenetic analyses, part of a general phylogenomics software suite.
Construction of supertrees and exploration of phylogenomic information from partially overlapping datasets. Implements optimal phylogenetic supertree methods.
Analyses single-copy phylogenetic trees to assess compatibility with user-defined groupings (clans) in unrooted trees — ideal for large-scale phylogenomic analyses.
Chris is coordinating Rumen-Innovate, a new €4.8 million Horizon Europe Marie Skłodowska-Curie Actions project bringing together 11 institutions and 19 industry and research partners to train the next generation of ruminant microbiome scientists and develop tools to reduce agricultural methane emissions. The Queen’s team also includes Professor Sharon Huws and Dr. Katerina Theodoridou.
Chris has been appointed to the UK Department for Science, Innovation and Technology’s new College of Experts, a network of independent specialists giving DSIT rapid, flexible access to leading scientific and technical expertise. He joins 71 members selected from nearly 1,200 applicants, launched formally at the Royal Society in London on 18 June 2026.
PhD student Emmet Campbell, with Timofey Skvortsov and Chris Creevey, developed Ptolemaea, a pipeline that reconciles bacterial antiviral (phage) defence-system annotations from PADLOC, DefenseFinder and a bidirectional BLAST search into a single consensus call per gene. Run across 700 genomes spanning E. coli and the ESKAPE pathogens, Ptolemaea recovered over 32,000 defence-system annotations, roughly twice as many as either existing tool alone, while making disagreements between tools explicit and resolvable. Preprint available on bioRxiv; the pipeline is freely available on GitHub.
We're always happy to hear from people curious about machine learning, computational biology, bioinformatics, and microbial genomics — whether you're looking for a PhD, a postdoc, or just want to talk science. Drop Chris an email.