Computer Models in the Biological Sciences
The biological sciences now make considerable use of computer models, and this use has rapidly increased over the last couple of decades. Glenn Rowe, in his book Theoretical Models in Biology: The origin of life, the immune system, and the brain (Oxford, 1994, vii), explains why:
The models that we examine are, for the most part, complex enough that they require computer simulation. Although there are many models in biology that do not use computer simulation (except possibly for numerical solution of differential or difference equations), it is the author's belief that these will form an ever-shrinking minority of those models that are capable of genuine application to biology. ... biological systems are inherently more complex than the inanimate systems of physics and chemistry, so that models that do not take account of this complexity cannot be considered realistic. ... It is only now that we have the ability to do complex calculations and simulations that we are discovering that a great many systems seem to have an inherent complexity that cannot be simplified. ... After another 300 years, we will no doubt feel as comfortable using computer simulations to analyse nature as scientists today feel using Newton's laws of motion to describe the trajectory of a falling stone.
Rowe's book, which covers the origin of life, the immune system, and the brain, illustrates some of the potential breadth of application of computer models in biology. Other particularly important areas include Bioinformatics, Systems Biology, Evolution, and Behaviour.
Bioinformatics is a term that can be used to cover a wide range of applications of information technology within the biological sciences, some of which (e.g. protein structure prediction) involve use of computer modelling, though others do not. Most characteristic is the use of massive databases of genetic and other data, with clever algorithms for exploiting the information they contain. Some uses of this information, particularly in a medical or legal context, raise interesting new ethical issues for the philosopher to consider.
In Systems Biology, the complexity of the interactions between the various physiological levels goes well beyond the bounds of traditional mathematical analysis, leaving the use of computer models as the practical method of detailed analysis. Denis Noble, long-time Professor of Cardiovascular Physiology at Oxford, has written a popular book, The Music of Life, in which he powerfully argues that such interactions require an approach that is neither "top-down" (from organism to organ to cell etc.) nor "bottom-up" (from gene to protein to cell etc.), but rather "middle-out". No one level of analysis is privileged in biological systems, where high-level properties can influence low-level processes and vice-versa. This rules out traditional analytical approaches, but progress can be made computationally, as Noble and his colleagues have demonstrated by developing a "virtual heart", which they have used to assess the likely effects of drugs and other treatments for cardiac disorders. For more on all this, see his Presentation on Systems Biology and the Virtual Heart.
Evolution and Behaviour
Study of interactions between organisms – as in Evolution or Behavioural Ecology – is very naturally carried out using using Agent-Based Models. These are now relatively easy to implement with modern computer tools and systems, so that even a researcher with modest technical abilities can aspire to build and test worthwhile models. Many examples of such models can be found in the collections of Agent-Based Models available through the previous link, but some of particular interest are linked below:
- Foraging Ants Model, by Uri Wilensky, based on a model from the MIT Media Lab
- Model of Flocking Behaviour (by Uri Wilenksky, CCL, based on Craig Reynolds' Boids)
- Model of Wolf-Sheep Predation (by Uri Wilenksky, CCL)
- Population Genetics in a Fishbowl, by Thomas C. Jones, Biological Sciences, East Tennessee State University