Foundation Modules (Year 1)

Main coursesAlternative
Cells, Signalling and Systems


This module introduces core concepts in molecular and cell biology for graduate students with a background in physical sciences. 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. (Duration: two weeks.)
Essential Mathematics and Statistics


This module introduces essential fundamental concepts and methods in mathematics, probabilistic modelling and statistical inference, focusing on their use for practical problems. It is aimed at students who have little formal training in mathematics beyond A-Level or equivalent. Through lectures during which questions and student participation are actively encouraged, in tandem with intense problem solving sessions, the topics of differentiation, integration, complex numbers, solution of linear ordinary differential equations, matrices, summarising data, probability models underlying data analysis, data modelling and hypothesis testing are all covered. (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 (C and Python), 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.
MATLAB – Scientific Computing for Biomedicine


The course introduces the core techniques in scientific programming for applications in biology and introduces students to the widely used Matlab programming environment. Areas covered include: basic statistical analyses and data summary; functions; numerical linear algebra; numerical solution of differential equations; discrete and stochastic modelling; analytical methods in applied mathematics including dimensional analysis and asymptotic methods; and principles of software engineering. Applications of MATLAB may include solving differential equations in ecology and physiology, medical image segmentation and some parallel computing. Problems draw on current research problems in biology ranging from the molecular to the population level. (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 agent-based modelling. The course will consider modelling of gene, metabolic and signalling systems. Case studies will include bacterial chemotaxis and synthetic oscillators, as well as a short project and presentation undertaken by the students. (Duration: two weeks.)
Introduction to Experimental Bioscience


This is a laboratory-based course that introduces some of the laboratory techniques used in experimental molecular and cell biology. Techniques covered include DNA extraction; DNA sequencing and manipulation; microbiological methods and sterile technique; protein expression, purification and characterisation; and microscopy and cellular imaging. (Duration: two weeks.)
Organic Chemistry


Introduces and develops the fundamental concepts of organic chemistry, from molecular structure to function; a theoretical and practical toolkit for understanding the chemistry of life and the design and synthesis of drug-like molecules. (Duration: two weeks.)