MSc Bioinformatics and Computational Genomics
Queen's University Belfast
Belfast, United Kingdom
Earliest start date
The past decade has seen enormous advances in molecular and biomedical technology resulting in an ‘omics’ revolution.
Bioinformatics covers the application of mathematics, statistics and computing to biological and clinical scenarios. Algorithms and software tools are used to understand and interpret patient-derived ‘Big Data’.
You will be analysing clinical and ‘omics data in order to find complex patterns relating to patient response to treatments and prognosis. You will discover results that translate to the real world, through clinical trials or commercialisation. 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 and clinicians from the Patrick G Johnston Centre for Cancer Research, the Welcome Wolfson Institute for Experimental Medicine, and the Centre for Public Health.
This is complemented by guest lectures from industrial and clinical collaborators.
Applicants are advised to apply as early as possible and ideally no later than 31st July 2022 for courses that commence in late September. In the event that any programme receives a high number of applications, the University reserves the right to close the application portal.
Please note a deposit will be required to guarantee a place on the course. Due to high demand, applications may not be considered if the course has reached its maximum class size and will be placed on a waiting list.
Bioinformatics And Computational Genomics Highlights
The analysis of ’Big Data' may 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.
- You'll be involved with our Patrick G Johnston Centre for Cancer Research, which works 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.
Internationally Renowned Experts
- You'll be involved with our Centre for Cancer Research and Cell Biology, which works 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.
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 the 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 studies in Bioinformatics at Queen’s and further afield. Others go on to work in a variety of roles in both the private and public sectors 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 Bioinformatics Scientist at Almac Group
- Bioinformatician at Fios Genomics Ltd
- Biomedical Scientist and Junior Bioinformatician, BioKinetic Europe
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 help our students gain key leadership positions both nationally and internationally.
Students may enrol on a full time (one year) basis. There is an introductory module to Cell Biology and Computational Analysis during the first two weeks. This is followed by three (20 CAT) modules in Semester 1, and four modules (2 x 20 CAT and 2 x 10 CAT) during Semester 2.
The MSc is awarded to students who successfully complete all taught modules (120 CATS) and a dissertation (60 CATS).
A Diploma exit qualification is available to those students who have successfully completed 120 CATS points of taught modules.
A Certificate exit qualification is available to those students who have successfully completed 60 CATS points of taught modules.
Bioinformatics and Computational Genomics is an interdisciplinary field at the heart of biomedical research, discovery and practice. With its challenging and rewarding content, this Master's degree will provide students, with a background in computational or life sciences, the opportunity to move into an exciting new area of discovery, technology and application. 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:
SCM8051 Analysis of Gene Expression – 20 CATS
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.
SCM8095 Genomics and Human Disease – 20 CATS
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.
SCM7047 Scientific Programming and Statistical Computing – 20 CATS
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.
SCM8148 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.
SCM8152 Systems Medicine: From Molecules to Populations (half module 10 CATS)
Students will develop knowledge of integrative approaches for multi-'omics biomedical data analysis in order to illuminate disease mechanisms, with applications in precision medicine. Systems medicine brings together multiple scientific disciplines; some of the key areas covered in this module are network biology, machine learning and patient stratification.
SCM8108 Applied Genomics – 20 CATS
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.
SCM8109 Biostatistical Informatics (online) – 20 CATS
The core of this module will highlight the analysis of clinico-pathological and 'omics' data. The module will also provide an introduction to carrying out key statistical tests in the R statistical programming language.
Research Project: Dissertation – 60 CATS
Translational bioinformatics and technical development research projects are mainly split between the Patrick G Johnston Centre for Cancer Research and the Wellcome Wolfson Institute for Experimental Medicine.
You will be taught by subject experts from the Patrick G Johnston Centre for Cancer Research (https://www.qub.ac.uk/research-centres/cancer-research/), the Wellcome Wolfson Institute for Experimental Medicine (https://www.qub.ac.uk/research-centres/wwiem/), and the Centre for Public Health (https://www.qub.ac.uk/research-centres/CentreforPublicHealth/). This is complemented by guest lectures from industrial and clinical collaborators.
You’ll be taught by active researchers including biologists, clinicians and bioinformaticians. 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.
Learning and Teaching
We provide a range of learning experiences that 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.
Assessments associated with the course are outlined below:
Assessment for the modules will be based on 100% 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.
Students who pass 60 CATS of modules are eligible for the award of PG Certificate.
Program Tuition Fee
English Language Requirements
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