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Cambridge Systems Biology Centre


Introductory module: This module starts with an Introduction that deals with the concepts, history, and future aspirations of systems biology. The module develops three interweaving sub-themes. You will have lectures that deal with the nature of modern biological science in relation to the concepts, approaches, methods and tools of Systems Biology. Following this, the teaching focuses on a contextualised mathematical and computer modelling toolkit comprising lectures and classes. The module runs in the first two weeks of the Michaelmas Term and comprises 29 lectures plus 8 computer-based practical sessions..


Data Acquisition and Handling (DAH): Systems biology relies on the ability to obtain a ‘global’ view of the physiology of a cell by the simultaneous identification and quantification of thousands of different molecules (such as proteins, nucleic acids and metabolites).  This module will present the techniques used to acquire data in the various ‘omics’ approaches (transcriptomics, proteomics and metabolomics), as well as in high-throughput genetics.  Because of their size and experimental limitations, the handling of these datasets presents unique challenges.  Therefore, the module will emphasise the practical aspects of dealing with this type of data.  Large-scale approaches are generally applied to cell populations, and often lack spatial and temporal resolution.  The module will introduce how they are complemented by in vivo analysis of single cells using advanced microscopy, which can provide information on cell-to-cell variation and spatial control. This Module will run in the Michaelmas Term and consist of 18 lectures plus 6 computer-based practical sessions.


Modelling and Analysis of networks (MAN): The module focuses on mathematical and statistical methods used to evaluate and analyse large-scale data sets and use them for the reconstruction of biological networks. Methods for the analysis of metabolic, gene-regulatory, and large-scale networks will also be introduced.

The module runs in the Lent Term and comprise of 15 lectures plus 10 computer-based practical sessions.


Modelling in Biology (MIB): This module aims to introduce students to the de novo design of biological systems using the techniques of Synthetic Biology and computational simulation. The theory and practice of Synthetic Biology is introduced both in the context of designing exemplar biological systems to test our understanding of natural systems and in that of systems design and fabrication to produce novel devices of commercial or medical utility. The design, simulation, and analysis of biological models using some of the main computational techniques in Executable Biology are then introduced. Finally, the two strands of the module are integrated by a group mini project in which students design a system and test its feasibility by computer simulation, or build a model of a particular biological process and analyse its behaviour.

The module will run in the Lent Term, and consists of 13 lectures and 5 computer-based practical sessions.


Seminars: One set of seminars will be in a journal club format, where students will present seminal papers from the field. There will be 10 such seminars, with two students presenting at each. In addition, there will be talks given by invited speakers. The second seminar format will involve small-group teaching sessions led by post-docs to review journal articles and consolidate course material. Overall, there will be a total of two one-hour seminars per week.


Research Project: The project will run for 12 weeks in Michaelmas and Lent Terms, starting in week 4 of Michaelmas Term. It may consist of any (agreed) combination of practical, theoretical or analytical work and will have support from classes or seminars from active researchers. Each project will have a research group leader as overall (senior) supervisor and a day-to-day supervisor (post-doctoral or senior graduate student). Joint projects will be encouraged where pairs of students, one with a biological and one with a mathematical/physical/computational background, collaborate to address a systems problem.  Students will present the results of their project to the group and submit individual project reports.

A list of project supervisors can be found here.