Learning and Inference in Computational and Systems Biology Workshop

In making advances within Computational Systems Biology there is an acknowledged need for the ongoing development of both probabilistic and mechanistic, possibly multi-scale, models of complex biological processes. In addition to such models the development of appropriate and efficient inferential methodology to identify and reason over such models is necessary.

Examples of the progress which has been made in our understanding of modern biology by the exploitation of such methodology include model based inference of p53 activity; uncovering the evolution of protein complexes and understanding the circadian clock in plants; details of which were presented at the LICSB workshops.

The previous workshop themes of parameter estimation, probabilistic modelling of networks and inference in large biological system models will be further explored in this meeting. Contributions of recent work addressing these themes as well as preliminary application results are welcomed.