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This subject introduces mathematical and computational modelling, simulation and analysis of biological systems. The emphasis is on developing models, with examples, using MATLAB.
Modelling biochemical reactions. Law of mass action. Enzymes and regulation of enzyme reactions. Thermodynamics of reversible biochemical reactions. Cellular homeostasis. Application of ordinary differential equations to these problems.
Modelling large reaction networks. Flux balance analysis and constraint-based methods. Genome-scale models. Regulation of gene expression. Gene regulatory networks in systems and synthetic biology. Network inference and statistical modelling of –omic data. Knowledge-based modelling in systems biology.
Intended learning outcomes
On completion of this subject the student is expected to:
- Evaluate the role for mathematical and computational modelling of biological systems;
- Employ the law of mass action to develop ODE models for biochemical reactions;
- Develop and analyse models for enzyme catalysed reactions in cellular bioengineering and synthetic biology;
- Demonstrate the use of ODE and PDE models in molecular and cellular physiology;
- Describe the premise of systems and synthetic biology;
- Develop and analyse large-scale network models for biosystems and synthetic biology;
- Explain the role of knowledge-based modelling in systems biology;
- Evaluate and employ the measurement technologies and sources of data underlying systems and synthetic biology, including data repositories and different modelling approaches.
On completion of this subject students should have developed the following generic skills:
- Ability to apply knowledge of science and engineering fundamentals.
- Ability to communicate effectively, with the engineering team and with the community at large.
- Capacity for lifelong learning and professional development.
- Profound respect for truth and intellectual integrity, and for the ethics of scholarship.
Last updated: 31 January 2024