Computational and Systems Biology I
Syllabus, Master's level, 1MB511
- Code
- 1MB511
- Education cycle
- Second cycle
- Main field(s) of study and in-depth level
- Molecular Biotechnology A1F, Technology A1F
- Grading system
- Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
- Finalised by
- The Faculty Board of Science and Technology, 7 March 2011
- Responsible department
- Biology Education Centre
Entry requirements
120 credits including Genome Biology
Learning outcomes
The aim of the course is to generate knowledge in quantitative modelling of biological systems at both a molecular and cellular level. After the course, the student should also understand how these models are used, analysed and developed. After passing the course the student should be able to
- Describe how protein folding happens from an energetic as well as a structural perspective
- Explain how structural determination of proteins are done using X-ray crystallography or nuclear magnetic resonance (NMR) experiments
- Describe intracellular chemical reactions using deterministic and stochastic models
- Analyse stability, bifurcations and stochastics in dynamic systems using analytical methods
- Describe the basic principles for how gene regulation, morphogenesis and signal transduction work on a physical level
Content
Methods for analysis of macromolecular three-dimensional structures including X-ray crystallography or nuclear magnetic resonance (NMR). The physical background to the structure and folding of biological macromolecules. Analysis of dynamic properties with the help of experimentally determined structures and computer simulations. Models to describe reaction kinetics, relaxation kinetics, diffusion and diffusion control, catalysis of enzymes and stochastic description of chemical reactions. Equilibrium and membrane transport: Membrane potential, ion transport, chemical osmosis. Irreversible thermodynamics: : Dissipation, accuracy, proof-reading. Analysis of non-linear dynamic systems: State space analysis, bifurcation theory, stability, oscillations, time-delayed regulatory systems, power-law formalism. Mesoscopic kinetics: The master equation, Gillespie algorithm, Linear noise approximation, and separation of time scales. Reaction-diffusion models. Principles of robust control systems for chemotaxis and morphogenesis. Principles for optimisation of gene expression regulation.
Instruction
Lectures, seminars and computer exercises.
Assessment
Written test 8 credits Hand-ins 3 credits Computer exercises 2 credits. Written and oral project presentation 2 credits.