Best suited to students with experience with statistics and machine learning concepts such as Markov models, maximum likelihood etc.
Description:
Description: A number of projects are available in collaboration with Prof David James at the Garvan Institute, to study various aspects of cell metabolism, insulin action and this system becomes defective leading to diseases such as diabetes. Our goal is to use Systems approaches to map the behaviour of the metabolic system under a range of physiological conditions. This will involve incorporating information from large data sets depicting gene expression, proteomics and metabolomics to construct a network map, identifying functional nodes and distinguishing between cause and effect responses. ONce established this model can be used to explore novel functionaslities, potential therapeutic modalities and disease loci. With the increasing availability of high-throughput technology such as microarrays generating genome-wide data sets, the opportunity arises to apply techniques of computational inference, visualization, etc. to generate executable models of biological activity from the data. A benchwork component is available if desired.
Contact supervisor (bgaeta@cse.unsw.edu.au). This project will be a collaboration with the Garvan Institute of Medical Research.
Comments:
This project is best suited to students with experience with statistics and machine learning concepts such as Markov models, maximum likelihood etc. Knowledge of cellular biology and metabolism is useful but not essential.
