Executable Biology

Pre-requisites

Knowledge of at least two of the following topics would be essential: automata theory, automated verification, process algebras, probability theory and differential equations. Familiarity with biology is not essential but would be an advantage.

Overview

Computational modelling of biological systems is becoming increasingly important in efforts to better understand complex biological behaviours. Executable Biology focuses on the design of executable computer algorithms that mimic biological phenomena in order to enhance biological comprehension. This course provides an in-depth survey of the main modelling approaches of Executable Biology, covering both theory and practical applications in biology. The aim is to familiarise students with the computational principles behind four modelling approaches - Boolean networks, compositional interacting state-machines, process calculi and hybrid systems - and give them an appreciation of how these methods can be used in biological research. Model analysis techniques such as simulation, animation and model checking will be covered. Examples of biological systems will include gene regulatory networks, circadian clocks, cell signalling crosstalk, and organs development.

Learning Outcomes

On completion, the students should be able to:

• Understand and apply the four computational modelling formalisms to specific biological systems.
• Appreciate the role of modelling and analysis of biological systems.
• Use computational modelling software tools.

Course Organisation

The course will be run in a one week intensive format, and will include 16 hours of lectures and 14 hours of exercise classes and/or practicals, plus approx. 40 hours of additional reading and/or familiarisation with software.