School of Mathematical Sciences

Bioinformatics

Modern biology is much more quantitative than the biology of the past, and is now critically dependent on the mathematical, physical and computer sciences. The School of Mathematical Sciences has a strong group of statistical bioinformaticians who conduct research in genomics, proteomics and systems biology in collaboration with biomedical researchers from government, universities and industry.

Researcher	Interests
Gary Glonek	Design and analysis of microarray and other experiments, Data mining, Statistical computing, Bayesian analysis, Analysis of categorical data, Biostatistics, Epidemiology
Inge Koch	Data mining, Multivariate analysis of high-dimensional data, Biostatistics
Andrew Metcalfe	Design of factorial microarray experiments, Statistics for hydrology modelling, Engineering statistics
Patty Solomon	Gene expression studies, Design and analysis of microarray and other experiments, Analysis of proteomic spectra, Gene and protein networks, Data mining, Components of variance, Biostatistics, Survival analysis, Clinical trials, Critical care medicine, Monitoring and assessing health outcomes, Epidemiology
Simon Tuke	Analysis of microarray data, Time course microarray experiments, Biostatistics, Statistical equivalence