MSc Bioinformatics and Computational Genomics

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

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 help our students gain key leadership positions both nationally and internationally.

Students may enroll 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 the analysis of gene expression data.

SCM8095 Genomics and Human Disease – 20 CATS

This module explores rapidly advancing fields that are moving from specialized 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 analyzing such datasets and gives practical experience in dealing with resulting datasets using relevant tools.

SCM8109 Biostatistical Informatics (online) – 20 CATS

The core of this module will highlight the analysis of clinicopathological 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.

Environment

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 in this course.

Learning and Teaching

We provide a range of learning experiences that enable our students to engage with subject experts and 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 in this course are lectures, practical experiences learning technologies, and self-directed study to enhance employability.

Assessment

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 percent 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 a PG Certificate.