Guest lecture by Peter Wellstead

CMBN is happy to announce the following guest lecture:

Guest lecture by Professor Peter Wellstead
Hamilton Institute
Republic of Ireland

Peter Wellstead is Science Foundation Ireland (SFI) Research Professor of Systems Biology, based at the Hamilton Institute. For full details see http://www.systemsbiology.ie/.

Lecture 2. September at 11.15am in room A3.3067, Rikshospitalet

Tittle: Analysing the Causes of Parkinson’s Disease: an energy systems approach
Summary of the lecture: Neurodegenerative diseases are among the most difficult conditions to study and analyze. For example, the causes of Alzheimer’s Disease and Parkinson’s Disease are unknown; they are hard to study in-vivo, and animal model and in-vitro studies are constrained by the complexity of the conditions and their apparent uniqueness to the human animal. Given these points, we claim that an in-silico systems approach, based upon mathematical modelling and control systems analysis, offers a valuable new framework for studying the complexities of these poorly understood diseases. Taking idiopathic Parkinson’s Disease (iPD) as the example, the talk will illustrate how the concept of a systems approach, originally developed for analysis of complex technological systems, can be used to build a systematic framework for disease study. The framework provides both an objective collection point for knowledge of the disease, and an analysis tool with which we can study the bio-dynamics and interactions that are potentially involved in disease causation.

Our systems approach is based upon a mathematical modelling of the process that allows the mind to function – namely the brain energy metabolism. A properly calibrated brain energy metabolism model is used as a core tool for analysis. This core can be built upon by attaching models of cellular sub-systems thought to involved in iPD causation. The potential role of these subsystems in iPD can then be examined by analysing their implications in-silico, together with the impact of weaknesses in the energy metabolism that supports them. In this way, the mathematical model provides an in-silico platform for disease study that:

1.  Complements practical experiments,
2.  Provides a quantitative, impartial repository of biological knowledge, and
3.  Forms a systems tool for the integrative analysis of possible disease mechanisms – including flaws in brain energy metabolism itself.

Current research interests:
Systems Biology – his personal interest is to contribute to a systems understanding of Parkinson’s Disease and other Neurodegenerative diseases.

Non-Invasive Sensing – in particular the use of his ACI technology for high throughput non-invasive medical and biological measurement.

System Identification

Control System Technologies in the Innovation process