This is a multidisciplinary research-based MSc course, designed for applicants with a biomedical, computational or mathematical background. It equips students with the necessary skills to produce effective research in computational genetics and bioinformatics. The course, which is based at the South Kensington campus, has been designed and is taught by staff from the Faculties of Life Sciences, Engineering (Computing), Physical Sciences (Chemistry, Mathematics) and Medicine. Teaching is by experts in relevant fields within the College but also makes use of collaborations with other researchers.

In the first term, students are provided with information not covered by their first degree courses, in addition to the following compulsory elements:

  • Bioinformatics and Systems Biology - Introduction to biology; advanced tools for the
    analysis of biological data; and approaches for modelling biological systems
  • Computing - Java, Python and perl; an introduction to program design and command line computing in a Unix shell
  • Mathematics and statistical inference - high level algorithms and the analysis of large datasets

The remainder of the year is devoted to three full-time research projects, undertaken under the supervision of researchers at Imperial College (this may also involve collaboration with other academic centres or industry).

More information

Course Structure

Autumn Term  (October - December)

In the first term, students will be provided with the supplementary information not covered by their previous degree courses or experience. This will be achieved through a basic specifically-designed and taught Bioinformatics (I) module and through computing and mathematics teaching which incorporates existing MSci and MEng modules, as well as specifically designed practical sessions.

Bioinformatics and Systems Biology I

The module covers the broad fields of Genetics and Genomics as core curriculum. In addition, a basic review of standard molecular biological concepts at 1st or 2nd year undergraduate level could be provided for students without a first degree in the biological sciences, supplemented by more extensive reading lists. Lectures and material will be designed to reinforce basic concepts and to introduce more advanced issues related to bioinformatics and computational biology.
Genetics will include: modes of inheritance (single-gene traits), chromosomal, somatic and mitochondrial disorders, complex trait disorders, linkage analysis for single gene and complex traits, linkage disequilibrium an animal models -advantages and limitations.
Genomics will include: physical mapping, the Human Genome Project, high-throughput sequencing, DNA and Protein databases (outline and principles), Principles of homology and motif identification (DNA and protein)

Probability theory, Information theory, Bayesian and frequentist methods, Descriptive analysis of large data sets
The basics of probability and statistics will be introduced, covering: axioms of probability, interpretations of probability, laws of probability, independence, discrete and continuous random variables, basic descriptive statistics, rudiments of estimation, basic notions of frequentist and Bayesian inference, and the descriptive analysis of large data sets. Practical experience will be gained through the use of an appropriate computer package.

Programming skills, Experience of DOS/Windows and UNIX/Linux, Basic computing concepts. The main elements will be:
Introduction to computing: This will be a general overview of computing techniques, including relational databases and SQL, computer architectures, features of programming languages.
Programming: Python/ Java/PERL
Program design: Program design, abstraction and modularity.
Associated assignments: Programming exercises will be designed to supplement the material covered and to give familiarity with both DOS/Windows and UNIX/Linux environments, and with the Perl scripting language.

Bioinformatics II
Bioinformatics: Theoretical and practical issues in bioinformatics research in the area of genome sequence and protein families will include: DNA sequence analysis and annotation, DNA alignment algorithms and DNA/protein homology and its uses, identification and delineation of protein families, phylogenetic analysis of protein sequences and residue conservation. Computational issues will include: Resources i.e. packages, programs, sites and tools, heterogeneous databases and interoperability.
Functional genomics: dealing with basics of experimental design and theoretical and practical bioinformatics issues arising from rapid developments in functional genomics, which will include: Analysis of whole genomes - eukaryotic and microbial genetics, gene function- pathways and signalling networks, transcriptional profiling- methods and analysis., proteomics- methods and analysis and methods and analysis of protein structure:
Statistical genetics: an introduction to theoretical and practical issues in current statistical genetics research and application including: Genetic epidemiology, segregation analysis and path analysis, parametric and non parametric linkage analysis, QTL analysis, linkage disequilibrium analyses and phylogeny and cladistics
Ethics and the law including: Ethical issues in contemporary genetics and patent law. In addition to the taught syllabus, practicals will be used to explore related issues more deeply. These practicals will focus on issues of direct relevance to industrial genomics/pharmaceutical practice including expression mapping, positional cloning, homology searching, sequence annotation, and pharmacogenomics.

Spring term (January - september)

projects (compulsory)

Research projects (January - September)

The research projects are designed to provide students with experience in implementing a substantive research project in Bioinformatics and to practise the skills they have learnt from the taught components of the MSc course. All projects will directly involve liaison with biologists, mathematicians, and computing specialists. All projects have a 10 -12 week duration.

Project one is a computing project, reinforcing programming skills and providing an opportunity to experience creation of code in detail.

Project two is a data analysis project which involves the students working on the statistical and computational analysis of biological or biomedical datasets in collaboration with experimental/clinical groups within Imperial College London. This should be related to ongoing research projects.

Project three is a bioinformatics and systems biology project, and provides a mechanism for use of the skills obtained during the course in a research environment. Students become part of their host laboratory within Imperial College, including associated hospitals and Silwood Park. Many of these projects contribute directly to scientific publications.

Students have plenty of opportunities to attend professional skills training run by the Graduate School: MasterClass.

How to Apply

Apply here

For further information email Mrs Jennifer Bennett

Links with Employers

Imperial College works closely with employers and industry, including Industrial Advisory Panels to design Master’s courses which provide graduates with technical knowledge, expertise and transferable skills and to encourage students to take internships and placements. All Master’s courses are designed with employer needs in mind with some Master’s courses accredited by Professional, Statutory and Regulatory Bodies.

Entry Requirements

Academic requirements

Applicants with a first degree in biological, physical, computational or mathematical courses, or equivalent overseas qualifications, are welcome to apply.

If your first degree is from a country other than the UK, you may find the guidelines within our Country Index helpful. Please note that these guidelines indicate the College minimum.

We particularly encourage graduates from numerical and physical sciences to join this programme.

The minimum qualification for admission is an Upper Second Class Honours (2:1) degree  from an UK academic institution or an equivalent overseas qualification.

 Extensive relevant work experience with a lower degree will be considered in special cases.

 The College also has a minimum English language requirement for postgraduate study; see more details.

 If you are in doubt about your eligibility, then do either make an enquiry or apply!

Fees and Funding