Special Issue "Entropy in Genetics and Computational Biology"
A special issue of Entropy (ISSN 1099-4300).
Deadline for manuscript submissions: closed (31 March 2010).
The concept of entropy arose in classical theoretical physics as describing a measure or randomness, or disorder, of a physical system. The second law of thermodynamics states that the entropy of a closed system increases with time: if a closed vessel initially contains hot air at one end and cold air at the other, then as time progresses the hot and cold air become increasingly mixed and this implies an increase in the entropy, or disorder, of the system. This is in effect a statistical law and in principle describes the most likely behaviour of the system. The huge number of atoms of air in the vessel implies however that this most likely behaviour is almost certain to arise, so that what is in principle a stochastic process can in practice be regarded as a deterministic one. In the biological world random events arise constantly, but here they are far more important than in the physical context just described. As just one example, the random transmission of genes from parent to offspring implies that the study of evolution as a genetic process must allow for this randomness. Thus this study involves quite complex mathematical stochastic processes, and developments in the theory of these processes have often been motivated by biological questions. Similarly advances in statistical theory have often, perhaps mainly, arisen in the biological and medical contexts. The analysis of medical data requires statistical methods to allow for the randomness inherent in the sampling process involved in obtaining these data. Thus entropy concepts, through statistics and stochastic process theory, pervade both medicine and biology.
Prof. Dr. Warren Ewens
- stochastic processes