Introduction to the special issue

Theory in Biosciences, Mar 2011

Jamie Davies, Michael Grinfeld, Steven D. Webb

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Introduction to the special issue

Jamie Davies 0 1 Michael Grinfeld 0 1 Steven D. Webb 0 1 0 M. Grinfeld S. D. Webb (&) Department of Mathematics and Statistics, University of Strathclyde , Glasgow, Scotland 1 J. Davies Centre for Integrative Physiology, University of Edinburgh , Edinburgh, Scotland - This special issue of Theory of Biosciences is the response to call for papers we circulated during and following the International Centre for Mathematical Sciences (ICMS) workshop on Emerging Modelling Methodologies in Medicine and Biology, held in Edinburgh July 20thJuly 24th, 2009. The aim of the meeting was to bring together modellers (mathematicians, physicists, computer-scientists, or engineers) attracted by the challenges and opportunities provided by twenty-first century life sciences, biologists with a synoptic view of their disciplines looking for over-arching explanatory schemes, and philosophers of science interested in the nature of biological systems, explanation, and understanding in biology. We thought that organising such a meeting was timely and important, because from the point of view of biology, we live in exciting times. New techniques for the investigation of life at the subcellular level appear all the time, and new data on the organisation and function of macromolecules are continuously collected. In the resulting increasingly and recursively involved picture, we need to uncover principles that govern this complexity. In many areas of science, notably in physics, mathematics has been successfully used to deal with complexity. The overarching aim of the meeting was to discuss foundational methodologies of the mathematisation of biology (Israel 1996). There is limited methodological work on modelling in biology; see for example (Fox-Keller 2000; Lander 2004), or the cautionary work in Buiatti (1998) and Rosen (1985). In biology, unlike physics, there are no discernible natural laws to anchor modeling to. In addition, biological systems are distinguished by being the product of evolutionary forces, and they persist in time while recycling and renewing their components. In biology it is very rare to have a system of a few interacting parts on the same scale: biological systems are complex, multi-scale systems by definition. Hence modelling a biological system is a highly nontrivial task. At the same time, mathematical formalism seems to be the only approach for dealing with the complexity of biological systems. There is a real need to confront this complexity, since in therapy, in principled drug design, or in ecosystem management it is often necessary to predict what the system as a whole would do in particular circumstances. The piecemeal methodology of experimental biology has no tools of its own to address this need. Complex systems, that is systems comprised of many tightly coupled heterogeneous (by nature and scale) components, can be approached in a number of ways. The reductionist way of an engineer is to decompose the system into simpler subsystems, analyse the workings of each subsystem separately, understand the coupling of the subsystems, and reconstruct in this way the function of the entire mechanism. This approach does not work in biology as it is not clear how, even in principle, to define a (reasonably closed) subsystem. So far, reductionist approaches in biology always leave open an explanatory gap between what the system does and what can with confidence be said about its parts. From the above remarks, the usefulness of a multidisciplinary approach to modelling in the life sciences should be clear. In the event, we had a very enthusiastic response from the modelling community and a strong showing from biologists in areas where some form of holistic approach is seen as necessary (ageing, cancer, developmental biology, structure of the nervous system). Unfortunately, for administrative reasons, we were not able to recruit as many philosophers of science as we would have wanted, and furthermore, all accepted papers in this special issue come from the modelling community. It seems to us that the set of fundamental questions we have identified (see http://www.icms.org.uk/workshops/ modellingmethodologies) is acutely relevant for developing successful applications of mathematical modelling in biology and medicine, and we hope that future meetings will realise our vision of a philosophically and biologically informed modelling activity. This special issue thus covers a variety of modelling approaches, encompassing both traditional techniques and a range of emerging methodologies. Differential equations form the main theme but these are approached, derived, and indeed used from a number of different angles. Examples include their application to a problem of energy metabolism at the whole organismal scale, their rigorous derivation using process algebra techniques, their coupling to bioinformatic data to provide a multifactorial network approach to model proteinprotein interactions and their applicat (...truncated)


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Jamie Davies, Michael Grinfeld, Steven D. Webb. Introduction to the special issue, Theory in Biosciences, 2011, pp. 1-3, Volume 130, Issue 1, DOI: 10.1007/s12064-010-0104-x