In recent years several different approaches to modeling the dynamics of biological processes have been developed, under a field that has come to be known as Systems Biology.
Recently there has been a growing interest in the application of hybrid systems techniques to biological modeling and analysis, since it has been observed that several biological processes exhibit the interaction of continuous and discrete phenomena. It has also been recognized that many biological processes are intrinsically uncertain; stochastic phenomena have in fact been shown to be instrumental in improving the robustness of certain biological processes, or in inducing variability. In this talk we will describe the development of a stochastic hybrid model for DNA replication, one of the most fundamental processes behind the life of every cell.
We will discuss how the model was instantiated for the fission yeast and present analysis results that suggest that the predictions of the model do not match conventional biological wisdom and experimental evidence. Interestingly, the problem appears to be not in the model, but in conventional biological wisdom. This has motivated follow-on experiments (in vitro and in silico) to test two competing biological hypotheses that could explain the mismatch.