Teachers: Russ Harmer, Gregory Batt, Vincent Danos, Samuel Bottani, Jerome Feret and Jean Krivine

Using novel experimental techniques, quantitative data can be obtained on the functioning of biological systems at the molecular level. The complete exploitation of this novel information on system dynamics requires a mode-based approach: models are proposed, analyzed and compared with respect to experimental data. Using models, various assumptions on biological mechanisms can be corroborated or invalidated by the experimental data on a rational basis. Experimentally-validated models can then be used to make novel predictions or orient system design.

Computational Biology 1
Teachers: Gregory Batt and Samuel Bottani

The objective of this course is to introduce the model-based approach of biological systems analysis from a practical point of view. The emphasis will be given on the modeling work, and on simple but important analysis methods. Such methods include state space analysis, global optimization for parameter search, and sensitivity analysis for robustness assessment.

Computational Biology 2
Teachers: Vincent Danos, Jerome Feret, Russ Harmer, and Jean Krivine

Students will learn a way to approach mechanistic modelling which is pretty different from the ODE world (at least seen from the outside) and much easier to get into for students with little background into dynamical systems. This kind of rule-based modelling technique approach has been hailed in a Feb 2011 Nature Methods news and views as "harbingers of an entirely new way of representing and studying cellular networks", and predicted to become within a decade "mainstream components of modern quantitative biology". So it is cool to be doing mainstream stuff with a decade as a head start.