Bioinformatics MSc

During this module you will develop an understanding of the key areas of genomics, human genetics and genetic variation. You will also examine the genomics basis of diseases and how it can be used to improve health outcomes.

On this module you will be introduced to basic practical sequence and structure analysis techniques, tools and resources. You will also develop a strong foundation in 'omics and NGS analyses. There will be opportunities for you to apply bioinformatics and computational analysis to problem-solving in real healthcare or industry scenarios.

On this module you will be introduced to data science in bioinformatics. You'll have opportunities to gain practical skills for programming such as Python and R. You will also be able to apply statistical and modelling techniques to explore big data, and design appropriate database and web solutions for computational biology and bioinformatics data storage, visualisation or dissemination.

This module will help you to develop knowledge and skills that underpin the clinical application of bioinformatics. The module will build on your genomics, bioinformatics and programming knowledge to develop an analysis strategy for a new service. There will also be opportunities for effective interdisciplinary team working.

This module will give you the chance to demonstrate your ability to organise and carry out a major piece of work. You will gather background information and research the literature and data . You will also design and execute a research plan to solve a bioinformatics problem, and discuss existing results and present your new findings through a series of written and oral presentations.

Machine learning is an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.

This module familiarises you with some basic machine learning algorithms and techniques and their applications, as well as general questions related to analysing and handling large data sets. Several software libraries and data sets publicly available will be used to illustrate the application of these algorithms. The emphasis will be thus on machine learning algorithms and applications, with some broad explanation of the underlying principles.

Data is revolutionising healthcare. The benefits of data when correctly used extend to patients, providers and board members, and the technology can make centralised patient management a reality. The aim of this module is to give you the knowledge and hands-on experience of developments in the broad range of data-driven healthcare.

Big data is a fast-growing field and skills in the area are some of the most in-demand today. Big data technologies cover a range of architectures, frameworks and algorithms designed to handle very large and often highly complex datasets.

The module will enable you to understand big data, its applications and associated issues for storing, managing, processing and analysing massive amounts of datasets, as well as become familiar with software tools and frameworks underpinning big data analytics.

You will also acquire the knowledge of statistical, mathematical and machine-learning techniques, and develop the ability to design and implement big data analytics modelling and applications to real-world problems.