Foundation Modules (First term)

Students will undertake a number of modules (including Research Skills and Induction courses) over the first year. These modules cover life science background and training in engineering, mathematical, computational and physical skills required for research in Synthetic Biology. The taught elements are delivered using an intensive module structure.

Core Modules

Cell and Systems I: This module introduces core concepts in molecular and cell biology for graduate students with limited molecular and cell biology background . Over the course of the module we introduce the building blocks of life and discuss how they interact in processes such as replication, metabolism, signal transduction and development. The course is taught through a combination of lectures, problem-solving exercises, hands-on laboratory exercises, discussions and independent study. Topics covered include: cell biology, DNA, replication, transcription and translation, protein structure and trafficking, signal transduction, metabolism, molecular genetics, epigenetics, genome engineering, evolution, neurobiology and molecular biology methods.

(Introductory Module. Duration: two weeks)

Essential Mathematics IA and IB: These modules are designed as an introduction for students with little direct maths teaching at University (IA) or have a stronger experience of maths but need a refresher (IB). Lectures, during which questions and student participation are actively encouraged, in tandem with intense problem solving sessions, will ensure students have the mathematical basis they need for the rest of the course. The topics include basic algebra revision, vectors, graphs; differentiation; integration; single ODEs; systems of 2 ODEs; complex numbers; permutations; combinations; matrix algebra; eigen-values & -vectors; intro to vector calculus; some sequences & series.

(Introductory Module. Duration: two weeks)

Programming and Software Carpentry: The programming module takes students from the very basics of how a computer works and the idea of an operating system, through to file and image processing. By presenting students with two programming languages, over the course of two weeks students will have learned how to select which language is appropriate for the problem in hand and how to tackle that problem. Skills presented include:

(Introductory Module. Duration: two weeks)

Cell and Systems II: This module introduces core concepts in molecular and cell biology for graduate students with a background in physical sciences. More emphasis will be placed on modelling, imaging and drug discovery.  Over the course of the module we introduce the building blocks of life and discuss how they interact in processes such as replication, metabolism, signal transduction and development. The course is taught through a combination of lectures, problem-solving exercises, hands-on laboratory exercises, discussions and independent study. Topics covered include: Cells; DNA; proteins; end of membranes– Signaling; cytoskeleton; neuroscience; Metabolism; Genetics; laboratory techniques; evolution; transcription and translation.

(Introductory Module. Duration: two weeks)

MATLAB – Scientific Computing: Revision of core mathematical techniques relevant to modeling in the life sciences, and basic introduction to scientific computing; stochastic simulation, and numerical solution techniques in continuous mathematics; programming in the MATLAB environment; taught at three levels: no previous experience, intermediate, and experienced; Applications in the interface between the physical sciences and biology. INTRODUCTORY WEEK: introduction to MATLAB and data analysis; Basic calculus in MATLAB; linear algebra; generalized linear models; principal component analysis; ordinary differential equations; coding standards and documentation; traveling waves instability; traveling waves and cellular automata; ADVANCED WEEK: profiling your code; Speeding up your code; Mex functions; high-performance MATLAB; image reconstruction techniques; and group projects.

(Introductory Module. Duration: two weeks)

Introduction to Systems and Synthetic Biology: This course is an introduction to the ideas and methods underlying Systems and Synthetic Biology modelling, including representative case studies. It introduces mathematical modelling of different types such as static network models, stoichiometric networks and dynamic modelling. The course will consider modelling of gene, metabolic and signalling systems. It will also discuss the number and types of “biological dials” that can be tuned to modify gene circuits to specification. Case studies will include bacterial chemotaxis and synthetic oscillators, as well as a short individual project. Delivery will be through traditional lectures, group activity sessions and group discussions.

(Core Module. Duration: two weeks)

Data Management, Analysis and Statistics for Bioscience: It is increasingly important that researchers consider how data is acquired, analysed, presented and stored. Such an understanding not only ensures that valid and worthy science is performed and creates impact but is also a requirement of publishers and funding agencies. This course will provide an introduction to best practice in scientific data management and curation, and to systems to help students curate, manage and publish experiments. We will discuss the challenges involved in data security, data curation and data sharing and strategies to address them. The course will also provide an introduction to advanced research computing as a means of accelerating computationally intensive tasks. The importance of the full consideration of statistics in the planning, execution and reporting of science will also be explained. Group exercises will provide experience of processing experimental data to produce ‘publication ready’ figures and text.

Topics to be covered include:

(Introductory Module. Duration: two weeks)

Introduction to Experimental Bioscience: Hands-on introduction to experimental techniques used in molecular and cellular biology, including the DNA extraction, PCR, mutagenesis, electrophoresis, PCR clean-up, DNA quantitation, DNA sequencing; Insight into the molecular processes underlying these techniques; training in experimental record-keeping; intellectual property; insight into the factors affecting experimental design, data generation data analysis; bioinformatics; Introduction to creation of scientific figures summarizing and presenting the experimental data. Experiment 1: human mitochondrial DNA; Experiment 2: forward genetic screening; Experiment 3: C. elegans and its mutants; Experiment 4: observing bacterial motility and chemotaxis; Experiment 5: protein electrophoresis and Western blotting; Experiment 6: heritable traits.

(Introductory Module. Duration: two weeks)