Bioinformatics and Biomathematics
Unit(s) of assessment: Allied Health Professions, Dentistry, Nursing and Pharmacy
Research theme: Medical Technologies and Advanced Materials
School: School of Science and Technology
The recent completion of the Human Genome Project and the advent of technologies such as DNA chips have revolutionised the life sciences, enabling biological processes to be studied far more comprehensively than was previously possible. A major focus of the Bioinformatics and Biomathematics group is the development of mathematical, statistical and computational approaches addressing some of the post genomic challenges.
The research focuses on the development of new mathematical approaches based upon matrix computations, computational graph theory, Kolmogorov’s complexity, Bayesian inference, computational statistics, continuum mechanics and dynamical systems theory for:
- discovering important structural and functional features within large real-world networks and understanding complex systems, particularly those arising in biology
- mining the data from post genomic technologies including, mass spectrometry, gene expression array and flow cytometry
- modelling mechanisms of mutations causing human genetic disease and cancer
- modelling soft tissue growth, sexually-transmitted infections, and tissue engineering.
The group has well established research collaborations with various institutions in the UK and abroad. It also provides bioinformatics and biomathematics expertise supporting both laboratory-based and in silico analyses currently being undertaken by the Neurobiology groups and the John van Geest Cancer Research Centre.
Skills/Techniques: expertise in Artificial Neural Networks, Bayesian inference and deep learning, modelling of tissue growth, analyses of mutation data, microbial genomics, 16S rRNA gene-based microbiota profiling, shotgun metagenomics,transcriptomics (prokaryote, eukaryote), metatranscriptomics, protein structural informatics.
- Professor Graham Ball - bioinformatics, artificial neural networks, systems biology, cancer
- Professor Nadia Chuzhanova - bioinformatics, algorithm design, complexity, computational statistics, mutagenesis
- Dr Jonathan Crofts - complex networks, dynamical systems, computational neuroscience, neuroinformatics
- Dr Golnaz Shahtahmassebi – dynamic models, Bayesian inference, computational statistics, particle filters.
- Dr Martin Nelson – biomechanics and multiscale modelling.
Selected publications are listed on staff members' profile pages