Overview

Genome sequencing technologies have become widespread in nearly all areas of biomedicine. They are routinely used in population genomics, microbiology, epidemiology, clinical diagnostics, and drug discovery.

Despite the relative ease of generating genomic data at scale, there is pressing need for experts in genome data interpretation.

This MSc in Computational Genomics is specifically designed to provide in-depth training in programming, statistics and genome sequence data analysis to graduates with degrees in biological science disciplines. It will provide you with a specialist education in this rapidly developing area and you will be well equipped to progress on to PhD studies or a career in academia or industry.

The six modules cover the basic principles of genetics and genomics, statistical techniques applied to genomics, programming for biological data analysis, and genome data analysis.

You will gain a thorough grounding in the Linux operating system and Python programming language, while R programming will be covered in the context of its application to statistical analysis and data visualisation. This course will also foster transferable skills such as scientific writing, analytical thinking, and presentation of research.

In the latter half of your studies, you will have the unique opportunity to participate in a six-month computational genomics research project in a world class scientific environment, under the supervision of experts in the field.

Structure 

This page reflects the latest version of the curriculum for this year of entry. However, this information is subject to change.

Find out more about the limited circumstances in which we may need to make changes to or in relation to our courses, the type of changes we may make and how we will tell you about changes we have made.

Page last reviewed on 25 October 2021.

Core modules

You will take all of the modules below.

Introduction to Genetics and Genomics

Learn fundamental concepts in genetics, genomics and the applications of next generation sequencing technology, building a necessary foundation for the rest of the course.

Python Programming for Bioinformatics

Discover Python, a simple and powerful programming language that is used for a wide range of scientific applications, and explore its practical applications. 

Quantitative Biology and Statistics

Study statistics as well as more advanced statistical and quantitative genomics methodologies.

Genome Data Analysis

Explore Next Generation Sequencing (NGS) data analysis, including processing and interpretation of whole genome, whole exome or gene panel datasets, as well as epigenomic data. 

Advanced Genome Data Analysis

Build on previous modules and explore systems thinking, required for translational and biological research. 

Computational Genomics Research Project

Join a research team to conduct a computational genomics research project and work on a real-world scientific project as a member of a research group under the supervision of experts in the field.

Entry requirements

We welcome students from all over the world and consider all applicants on an individual basis.

How to apply

Tuition fees and funding

The level of tuition fees you pay is based on your fee status, which we assess based on UK government legislation.

Find out more about fees and funding opportunities.

Fees for 2022 entry

Studying at Imperial

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