Postgraduate Course: Computational Systems Biology (INFR11039)
|School||School of Informatics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Available to all students
|Summary||Systems Biology is the application of computational modelling and simulation to complex systems in biology. Examples include biochemical pathways, metabolic processes, protein complexes and information processing, genetic networks, self-organising systems, neuronal networks and cell-cell communication. This course will focus on the level of molecular and genetic systems and simulations.
The course will be start with a series of core lectures introducing the main topics and will be complemented by home excersizes on simulations. The later half of the course will focus on exploring existing models, how they were established, their value and their limitations.
* Packages and methods for simulations
* Dynamics and design of cellular reaction networks
* Metabolic pathway analysis
* Network architecture
* Genetic regulatory networks
* Protein complexes
* Self-organisation in cellular systems
* Application of modelling and simulation to drug discovery
* Systems Biology Mark-up Language
Relevant QAA Computing Curriculum Sections: Data Structures and Algorithms, Developing Technologies
Entry Requirements (not applicable to Visiting Students)
|| Students MUST have passed:
Bioinformatics 1 (INFR11016)
||Co-requisites|| It is RECOMMENDED that students also take
Bioinformatics 2 (INFR11005) OR
Models and Languages for Computational Systems Biology (INFR11047)
||Other requirements|| For Informatics PG and final year MInf students only, or by special permission of the School.
Bioinformatics 1 (or strong biological background).
Students are expected to have: - basic biological knowledge (BIO1 course) - basic mathematical knowledge of differential equations and linear algebra - basic programming skills, in any language.
Information for Visiting Students
Course Delivery Information
|Not being delivered|
| 1 - Discuss the potential benefits and predictive value of systems biology approaches.
2 - Implement a molecular genetic model in an appropriate modelling framework.
3 - Compare and contrast existing models at the biochemical, genetic, proteomic and metabolic levels
4 - Discus the methods used to establish parameters in models and how to test and refine them.
5 - Discuss the mathematical basis for biomolecular simulations.
6 - Describe the limitations of modelling strategies.
|* Edda Klipp, Systems Biology in Practice, Wiley-VCH, 2005.|
* Athel Cornish-Bowden, Enzyme kinetics / Oxford : IRL, 1988.
* David Fell, Understanding the Control of Metabolism: Portland Press, 1997.
* David L. Nelson, Lehninger principles of biochemistry / 4th ed., W.H. Freeman, 2005.
* Basic Mathematics for Biochemists, Athel Cornish-Bowden, Oxford University Press.
Kinetic Modelling in Systems Biology, Demin & Goryanin
|Course organiser||Dr Michael Rovatsos
Tel: (0131 6)51 3263
|Course secretary||Miss Kate Weston
Tel: (0131 6)50 2692