Wellstead, Peter (2007) The Role of Control and System Theory in Systems Biology. In: 10th International Federation for Automatic Control (IFAC) International Symposium on Computer Applications in Biotechnology, June 4-6 2007, Cancun, Mexico. (Unpublished)
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Abstract
The use of new technology and mathematics to study the systems of nature is
one of the most significant scientific trends of the century. Driven by the need for
more precise scientific understand, advances in automated measurement are providing rich new sources of biological and physiological data. This data provides
information with which to create mathematical models of increasing sophistication and realism - models that can emulate the performance of biological and
physiological systems with sufficient accuracy to advance our understanding of
living systems and disease mechanisms.
New measurement and modelling methods set the stage for control and systems theory to play their role in seeking out the mechanisms and principles that
regulate life. It is of inestimable importance for the future of control as a discipline that this role is performed in the correct manner. If we handle the area
wisely then living systems will present a seemly boundless range of important
new problems - just as physical and engineering systems have done in previous
centuries. But there is a crucial difficulty. Faced with a bewildering array of
choices in an unfamiliar area, how does a researcher select a worthwhile and
fruitful problem? This lecture is an attempt to help by offering a control oriented guide to the labyrinthine world of biology/physiology and the control
research opportunity that it holds.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Edited Text of a Plenary Lecture presented at the 10th International Federation for Auto- matic Control (IFAC) International Symposium on Computer Applications in Biotechnology and the 8th IFAC International Symposium on Dynamics and the Control of Process Systems, June 2007. |
Keywords: | Control; System Theory; Systems Biology; Automated measurement; Modelling; |
Academic Unit: | Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 3647 |
Depositing User: | Hamilton Editor |
Date Deposited: | 08 May 2012 14:33 |
Refereed: | No |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/3647 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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