The Complex Adaptive Systems Approach to Biology

Statistical physics has accustomed us to mathematical descriptions of systems with a large number of components. The thermodynamic properties of ideal gases were understood as early as the end of the 19th century, while those of solids were understood at the beginning of the 20th century. In both cases, two important properties make modeling easy: B These are systems in which all of the components are identical. B If the interactions between the components are very weak, they can be ignored, as in the case of ideal gases. Otherwise, as in the case of solids, we can use linearization methods to put the problem into a form in which these simplifications can be made. These early successes compared to the difficulties encountered in the understanding of biological systems would make us consider the above mentioned systems as rather simple. On the other hand, here are some examples of complex living systems: B The human brain is composed of approximately ten billion cells, called neurons. These cells interact by means of electrico–chemical signals through their synapses. Even though there may not be very many different types of neurons, they differ in the structure of their connections. B The immune system is also composed of approximately ten billion cells, called lymphocytes with a very large number of specificities which interact via molecular recognition, in the same way as recognition of foreign antigens. B Even the metabolism of a single cell is the result of the expression of a large number of genes and of the interactions among the gene products. Although complexity is now a somewhat overused expression, it has a precise meaning within this text: a complex system is a system composed of a large number of different interacting elements . In fact, the great majority of natural or artificial systems are of a complex nature, and scientists choose more often than not to work on systems simplified to a minimum number of components, which allows him or her to observe “pure” effects. The complex systems approach, on the other hand, is to simplify as much as possible the components of a system, so as to take into account their large number. This idea has emerged from a recent trend in research known by physicists as the physics of disordered systems .