The Creevey Lab conducts cutting-edge computational biology research across multiple interconnected themes, leveraging microbiome data, genomics, and machine learning to address critical challenges in health, food security, and environmental sustainability.
¶ Multi-Drug Resistance Evolution and Transmission
Understanding how antimicrobial resistance develops and spreads across human, animal, and environmental microbiomes using computational approaches and phylogenetic analysis.
Investigating the intended and unintended consequences of antimicrobial policies and interventions on microbial communities.
Developing artificial intelligence solutions to transform agri-food systems for sustainability and resilience.
Using computational approaches to improve animal health, productivity, and environmental impact.
Applying large-scale microbiomics and machine learning to enhance early diagnosis and treatment of infectious diseases.
¶ Pathogen Detection and Safety
Developing computational tools for pathogen identification and safety assessment in clinical and forensic contexts.
¶ Phage Therapy and Environmental Management
Exploring bacteriophage applications for sustainable environmental solutions and biotechnology.
¶ Methanogen Biology and Climate Change
Investigating methane-producing microorganisms to understand and mitigate greenhouse gas emissions.
Creating novel bioinformatics tools and methodologies for microbiome and genomics research.
Core Technologies:
- Phylogenetic analysis algorithms
- Metagenomics pipelines
- Machine learning frameworks
- Comparative genomics tools
Developing approaches to integrate multiple types of biological data for comprehensive understanding of microbial systems.
Technical Focus:
- Metataxonomic and metagenomic data integration
- Proteomics and genomics correlation
- Systems biology approaches
Our research operates within a One Health framework, recognizing the interconnectedness of human, animal, and environmental health.
Integration Across:
- Clinical applications
- Agricultural systems
- Environmental monitoring
- Food safety
Bridging the gap between fundamental computational biology research and real-world applications.
Translation Pathways:
- Academic-industry partnerships
- Clinical implementation
- Policy-relevant research
- Technology transfer
- Antimicrobial Resistance Surveillance - Developing computational frameworks for tracking resistance evolution
- Sustainable Agriculture - AI-driven solutions for food system transformation
- Clinical Microbiomics - Machine learning for diagnostic applications
- Environmental Biotechnology - Phage-based environmental management
- Synthetic Biology - Engineered bacteriophage therapies
- Climate Change Mitigation - Microbiome-based solutions for methane reduction
- Precision Agriculture - Microbiome-informed farming practices
- Digital Health - Computational tools for personalized medicine
Our research inherently requires collaboration across:
- Computer Science and AI
- Microbiology and Ecology
- Clinical Medicine
- Agricultural Sciences
- Environmental Engineering
¶ 🎓 Training and Capacity Building
Current doctoral research projects span all major themes, providing comprehensive training in:
- Computational biology methods
- Microbiome analysis techniques
- Machine learning applications
- One Health approaches
- Software development and distribution
- Protocol and methodology sharing
- Training workshops and tutorials
- Public engagement activities
- AI-Microbiome Integration: Advanced machine learning for microbiome prediction and manipulation
- Global Health Applications: Scaling solutions to address worldwide challenges
- Climate-Smart Agriculture: Microbiome-based strategies for climate adaptation
- Precision Environmental Management: Targeted interventions for ecosystem health
- Real-time microbiome monitoring systems
- Automated analysis pipelines
- Cloud-based computational platforms
- Mobile diagnostic tools
¶ 📈 Impact and Applications
- Novel computational methodologies
- Open-source software tools
- High-impact publications
- Training next-generation researchers
- Improved disease diagnosis and treatment
- Sustainable food production
- Environmental protection
- Enhanced food safety
This page reflects our current research portfolio and is updated regularly to showcase evolving research priorities and emerging collaborations.