There are numerous examples of the importance of stochastic effects at various levels of biological organization, ranging from the extinction of family names with a predictable probability at the population level, to phenotypic differences between genetically-identical individuals due to random variations in the number of key enzymes, transcription factors, or other molecules.
Advances in molecular biology, particularly in gene control networks, has stimulated a great deal of research aimed at understanding the role of stochastic effects in complex biochemical networks. A large class of problems involves linear or unimolecular reactions, and for these a more or less complete analysis of their behavior was given in our 2005 article in the bulletin.
The significance of the results lie in the fact that linear systems can now be fully understood, and the analytical results provide a test bed for approximation methods and algorithms.
To find out more check out www.sciencedirect.com/science/article/pii/S0092824004001247
Hans G Othmer is a Professor of Mathematics at the University of Minnesota, Minneapolis, MN, USA. For more information, visit his website: www. math. umn. edu/ ~othmer