Teachers: Gregory Batt (firstname.lastname@example.org) and Jacob Ruess (TA)
Schedule: 12 sessions of 3 hours. Weekly sessions are generally composed of 2-hour lectures and 1-hour lab sessions. A final oral presentation is planned in January.
Evaluation: The course grade will be based on assiduity and participation, three written reports on lab sessions and the written report and oral defence of the final exam. The final exam will be a joint exam with other courses.
Overview of the course:
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 model-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. 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 modelling 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. In addition we will investigate how to model biological variability observed at the molecular and cellular levels.
«Instilling in students the feel for biological systems and for models that are used to explore them»
- Testing the consistency of quantitative data produced in labs and current understanding of the functioning of the observed process
- Basic understanding of modelling: how to represent reality using mathematical notions
- Basic skills of analysis: numerical simulation, robustness, parameter search
- Notions on how to model biological variability
This course is made for people *not* familiar with biomolecular process modelling, dynamical system analysis, or Matlab programming. The sole requirements are therefore elementary calculus and notions of molecular and cellular biology, as well as a strong motivation to learn.
– Systems Biology in Practice: Concepts, Implementation and Application, by E Klipp, R Herwig, A Kowald and C Wierling, Wiley, 2005
– Mathematical modeling: bridging the gap between concept and realization in synthetic biology, by Y. Zheng and G.0 Sriram, Journal of biomedicine & biotechnology, 2010