PharmacoInformatics Laboratory
Head of laboratory:
Research foci:
- Computationally intensive methods in biostatistics and machine learning for analysis and modelling of biomedical data
- Heart rate variability for detection of changes in autonomic feedback function
- Modelling classification schemes for retinal ganglion cell photomicrographs
- Heart rate variability in type 1 and 2 diabetes
- Machine learning algorithms for analysis of bioinformatic data
The PharmacoInformatics laboratory conducts in silico biological research. Computational methods are applied to biological problems of interest to pharmacology. Computerised data management, machine learning and complexity analysis are our research tools. A wide range of biological and medical phenomena from cell classification to the progression of Alzheimer's disease, diabetes and cancer are "under the microscope" in the PharmacoInformatics Laboratory.
In an address to a symposium entitled "Accelerating Mathematical-Biological Linkages" at the National Institutes of Health, Bethesda, MD USA in 2003 Dr Joel Cohen said "Mathematics is biology's next microscope only better and biology is mathematics' next physics only better." By examining biological data mathematicians can study systems of greater complexity than can be constructed artificially. Conversely through the employment of advanced mathematical techniques explanations for a wide variety of biological phenomena can be found. Science has much to gain from the marriage of the mathematical and biomedical disciplines.
