Bioinformatics and Biomathematics
The recent completion of the Human Genome Project and the advent of technologies such as DNA chips have revolutionised the life sciences, enabling the biological processes to be studied far more comprehensively than was previously possible. A major focus of Bioinformatics and Biomathematics group is the development of mathematical, statistical and computational approaches addressing some of the postgenomic challenges.
Dr Jonathan Crofts' research focuses on development of new mathematical approaches based upon matrix computations, computational graph theory spectral graph theory, data-mining and the theory of random graphs for discovering important structural and functional features within large real-world networks and understanding complex systems, particularly those arising in biology.
Dr Reuben O'Dea's research concentrates on mathematical modelling of in vitro tissue growth, employing a range of modelling approaches to analyse the processes underlying observed tissue growth phenomena. Specific investigations include the influence of mechanical stimulation and bioreactor geometry on cell phenotype, and the development of tissue-scale models which represent underlying discrete microscale phenomena, such as cell signalling events.
Dr Timothy Hetherington is interested in various types of graph colouring problems. Particular areas of focus include list-colourings and arboricity. As well as publications in these areas he has also helped on a study that compares different sets of genes from different bacterial strains.
Professor Graham Ball has developed bioinformatics techniques based on Artificial Neural Networks for the modelling, analysis and data mining of data from post genomic technologies including, mass spectrometry, gene expression array and flow cytometry. The methods developed have application for biomarker discovery and identification as well as for the modelling of biological pathways in the context of disease systems. These approaches have been applied to the analysis of data from Alzheimer's disease, breast cancer, prostate cancer, cardiac disease and fruit ripening.
The research of Professor Nadia Chuzhanova revolves around in silico determination of the mechanisms underlying a wide range of mutations causing human genetic disease and cancer with the aim to identify mutations (and corresponding DNA sequence features) that are likely to exert an effect on tumour development and/or progression (i.e. to be driver mutations). She is particularly interested in the role of non-B DNA forming sequences in mediating mutational events including gene conversion and speciation in an evolutionary context.
