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Review Article |
1 Centre for Mathematical Biology, Mathematical Institute, University of Oxford, 24–29 St Giles, Oxford, OX1 3LB, UK2 Bioengineering Institute, University of Auckland, Private Bag 92019, Auckland, New Zealand3 University Laboratory of Physiology, Parks Road, Oxford, OX1 3PT, UK
Bioengineering analyses of physiological systems use the computational solution of physical conservation laws on anatomically detailed geometric models to understand the physiological function of intact organs in terms of the properties and behaviour of the cells and tissues within the organ. By linking behaviour in a quantitative, mathematically defined sense across multiple scales of biological organization – from proteins to cells, tissues, organs and organ systems – these methods have the potential to link patient-specific knowledge at the two ends of these spatial scales. A genetic profile linked to cardiac ion channel mutations, for example, can be interpreted in relation to body surface ECG measurements via a mathematical model of the heart and torso, which includes the spatial distribution of cardiac ion channels throughout the myocardium and the individual kinetics for each of the approximately 50 types of ion channel, exchanger or pump known to be present in the heart. Similarly, linking molecular defects such as mutations of chloride ion channels in lung epithelial cells to the integrated function of the intact lung requires models that include the detailed anatomy of the lungs, the physics of air flow, blood flow and gas exchange, together with the large deformation mechanics of breathing. Organizing this large body of knowledge into a coherent framework for modelling requires the development of ontologies, markup languages for encoding models, and web-accessible distributed databases. In this article we review the state of the field at all the relevant levels, and the tools that are being developed to tackle such complexity. Integrative physiology is central to the interpretation of genomic and proteomic data, and is becoming a highly quantitative, computer-intensive discipline.
(Received 21 October 2003;
; first published online 5 November 2003)
Corresponding author P. Hunter: Bioengineering Institute, University of Auckland, Private Bag 92019, Auckland, New Zealand. Email: p.hunter{at}auckland.ac.nz
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