Bioinformatics & Computational Genomics

The past decade has seen enormous advances in molecular and biomedical technology resulting in the 'omics' revolution.

Bioinformatics covers the application of mathematics, statistics and computing to biological and clinical scenarios. It involves the application and development of algorithms and software to understand and interpret 'Big Data', which is driving medical research, discovery and practice.

You will be looking at clinical and omics data to find complex patterns, which relate to patient response to treatments and prognosis. You will discover results that translate to the real world, through commercialisation or clinical trials to tackle diseases. You will use your vision to find unique solutions to clinical and biological problems, and by the end of the degree you will be ready to work within a multidisciplinary team alongside bioinformaticians, biologists (, the Centre for Experimental Medicine (, and the Centre for Public Health ( This is complemented by guest lectures from industrial and clinical collaborators.

Bioinformatics and Computational Genomics highlights
'Big data' can provide the key to unlocking the cause and development of various diseases, such as cancer. It also, offers the prospect of developing new drugs and therapies to prevent and treat conditions and diseases.

Global Opportunities
•The partnership with the National Cancer Institute (NCI) and the School of Medicine, Dentistry & Biomedical Sciences provides opportunity to study in the USA. This 4-year Doctoral Training Programme (DTP) provides students the opportunity to undertake a postgraduate taught programme in Year 1 at QUB (refer to link below for full list of programmes), followed by a PhD at NCI in Years 2-4. Further information is available at:

Internationally Renowned Experts
•You'll be involved with our Centre for Cancer Research and Cell Biology, who work with partners around the world in developing cancer treatments and pioneering advances in patient care. The Centre has an international reputation for successful dissemination and application of cutting edge research , knowledge transfer and the commercialisation of research ideas and innovations.

Learning and Teaching
We provide a range of learning experiences which enable our students to engage with subject experts, develop attributes and perspectives that will equip them for life and work in an advanced society making use of innovative technologies.

Across a combination of morning and afternoon classes, examples of the opportunities provided for learning on this course are lectures, practical experiences learning technologies and self-directed study to enhance employability.

Entry requirements

Entrance requirements
A 2.1 Honours degree or equivalent qualification acceptable to the University in a Natural Science subject, Mathematics, Computer Science, or a relevant medical or life sciences subject (e.g. Genetics, Molecular Biology, Biomedical Sciences, Physics or Statistics). A medical (MB) or dental degree (BDS) is also considered.

Intercalating Applicants
Intercalating medical and dental students within QUB will also be considered if they have successfully completed the 3rd/4th year of their course at first attempt and achieved at least an upper second class honours standard. Intercalating applicants should also ensure they have permission to intercalate from either the Director for Medical Education or Dentistry as appropriate.

An external medical or dental student wishing to intercalate must be ranked in the top half of their year cohort to have their application considered. Applicants must have passed all assessments at first attempt for the year in which they are applying (normally 3rd or 4th year).

International Students
For information on international qualification equivalents, please check the specific information for your country.

English Language Requirements
Evidence of an IELTS* score of 6.5, with not less than 6.0 in any component, or an equivalent qualification acceptable to the University is required. *Taken within the last 2 years

International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see:

If you need to improve your English language skills before you enter this degree programme, INTO Queen's University Belfast offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.
•Academic English: an intensive English language and study skills course for successful university study at degree level
•Pre-sessional English: a short intensive academic English course for students starting a degree programme at Queen's University Belfast and who need to improve their English.


1 year full-time.

Careers or further progression

Career Prospects
The rapid production of 'omics' data within medicine and the life sciences has meant that individuals with analytical experience in this field are highly sought after. Recent graduates have gone on to work in industry in companies such as Almac Diagnostics, Biokinetic Europe and Fios Genomics and some have gone onto further PHD level research.

Employment after the Course
Many of our students go on to pursue further PhD study in Bioinformatics at Queen's and further afield. Others go on to work in a variety of roles in both the private and public sector here in Northern Ireland and internationally. The following are some of the jobs they have taken on:

Bioinformatician at Belfast Health and Social Care Trust
Application Scientist at Dotmatics
Network and Security Engineer at Darktrace
Junior Bioinformatic Scientist at Almac Group
Bioinformatician at Fios Genomics Ltd
Biomedical Scientist and Junior Bioinformatician, BioKinetic Europe

Professional Opportunities
Queen's postgraduates reap exceptional benefits. Unique initiatives, such as Degree Plus and Researcher Plus bolster our commitment to employability, while innovative leadership and executive programmes alongside sterling integration with business experts helps our students gain key leadership positions both nationally and internationally.

Further enquiries

Dr Jaine Blayney 

Subjects taught

A fascinating and challenging set of subjects, this Masters degree will provide students with a background in computational or life sciences, to move across to an exciting new area of discovery, technology and applications.
We provide a broad learning base and offer training in open-source programming languages commonly used in academia and industry.

You will begin with an introductory short course (two weeks at the beginning of the first semester) in Cell Biology, followed by compulsory modules in:

Analysis of Gene Expression
This module will provide the practical molecular biological knowledge required to develop the most effective and useful computational tools for analysis of gene expression data.

Genomics and Human Disease
This module explores rapidly advancing fields that are moving from specialised research areas to mainstream medicine, science and public arenas. The principles of genomic medicine will be discussed alongside bioinformatics approaches for identifying 'causative genes' for human disease.

Scientific Programming and Statistical Computing
This module covers the fundamental elements of the statistical framework R and the programming language Python. It gives an introduction to parallel processing applications and implementation and how to leverage modern big-data problems through HPC computing.

Health and Biomedical Informatics and the Exposome (half module 10 CATS)
The module will cover different aspects of health informatics including the basic structure of electronic health records (EHRs). This module also includes an introduction to the concept of the exposome and the contribution of biomedical informatics in exposome research.

Digital Pathology for Bioinformaticians (Blended learning, half module 10 CATS)
In this module students will acquire the knowledge and skills to understand the principles of digital pathology within the context of precision medicine and companion biomarker development, focusing on how cancer research can benefit from digital and analytical technologies. The course will also focus on application of digital image analysis for rapid biomarker analyses.

Applied Genomics
This module examines the practical challenges in generating different 'omics' datasets, the important implications of how this is conducted when analysing such datasets and gives practical experience of dealing with resulting datasets using relevant tools.

Biostatistical Informatics (Blended learning)
The core of this module will highlight the analysis of different 'omics' data, including pre-processing, normalisation and quality control. The module will also provide an introduction to carrying out statistical tests in the R statistical programming language.

Research Project: Dissertation
Translational bioinformatics and technical development research projects are mainly split between the Centre for Cancer Research and Cell Biology and the Centre for Experimental Medicine. You will be working with supervisors who are actively conducting research into the causes and treatments of disease. There are also opportunities to work on research projects with our industrial partners.

You will be taught by subject experts from the Centre for Cancer Research and Cell Biology (, the Centre for Experimental Medicine (, and the Centre for Public Health ( This is complemented by guest lectures from industrial and clinical collaborators.

During the research projects, you may have the opportunity to work alongside PhD students in an open-plan environment on-campus, but the course is flexible. A suite of high-specification PCs is available for use by students on this course.

You'll be taught by active researchers including biologists, clinicians and bioinformatician. We also have teaching input from our industrial partners.

During the research projects, you may have the opportunity to work alongside PhD students in open-plan environments on-campus, but the course is flexible. A suite of high-specification PCs is available for use by students on this course.

Assessment method

Assessment for the modules will be based on 100 per cent coursework/in-class tests/dissertation.

Students who pass all of the taught modules but who fail to achieve a mark of at least 50 per cent in the dissertation are eligible for the award of a PG Diploma.

Application date

How to Apply
Apply using our online Postgraduate Applications Portal and follow the step-by-step instructions on how to apply.

Enrolment and start dates

Entry year 2020

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