Bioinformatics

Entry requirements

2.1 Hons (or non-UK equivalent) in Genetics, Molecular and Cellular Biology, Biochemistry, Biomedical Sciences, or other Life Sciences, with modules in Genetics and Molecular Biology at an average grade of 2.1 or non-UK equivalent.

We may also accept degrees in Computing Science, IT, Maths, Statistics, and Life Sciences subjects that do not fulfil core module requirements.

We may sometimes accept degrees at 2.2 Hons (or non-UK equivalent), if higher scores have been achieved in the subjects listed above, or in other relevant modules.

Months of entry

September

Course content

Bioinformatics is a discipline at the interface between biology, computing and statistics and is used in organismal biology, molecular biology and biomedicine. This programme focuses on using computers to glean new insights from DNA, RNA and protein sequence data and related data at the molecular level through data storage, mining, analysis and graphical presentation - all of which form a core part of modern biology.

Why this programme

• Benefit from being taught by scientists at the cutting edge of their field with intensive, hands-on experience in an active research lab during the summer research project.

• Emphasis is placed on understanding core principles in practical bioinformatics and functional genomics, then implementing that understanding in a series of practical elective courses in semester 2 and a summer research project.

• Accredited by the Royal Society of Biology for the purpose of meeting, in part, the academic and experience requirement

• Equips you with understanding and hands-on experience of both computing and biological research practices relating to bioinformatics and functional genomics.

• Based in the College of Medical, Veterinary & Life Sciences, which has carried out internationally-leading research in functional genomics and systems biology. It’s an ideal environment in which to train.

• Gain practical experience of working with large molecular datasets, with semester 2 courses built around real research scenarios, enabling you to see why each scenario uses the particular approaches it does and how to go about organising and implementing appropriate analysis pipelines.

• Advanced biocomputing skills are now deemed essential for many PhD studentships/projects in molecular bioscience and biomedicine, and are of increasing importance for many other such projects. We have also updated the programme to cater more readily for those interested in preparing for life sciences PhD projects.

• We welcome many students pursuing a career in Bioinformatics and several alumni now have careers in the field.

• Learn computer programming in Python, a language used in many areas of bioinformatics and biological computing

• Some of the teaching and research scenarios you’ll be exposed to reflect the activities of 'Glasgow Polyomics', a world-class omics facility set up within the university in 2012 to provide research services using microarray, proteomics, metabolomics and next-generation DNA sequencing technologies.

• Scientists here have pioneered the 'polyomics' approach, in which new insights come from the integration of data across different omics levels. Courses run by GP staff also provide a glimpse of 'systems biology' thinking - we see this as an important approach to the analysis of biological problems.

• We have several world-renowned research centres at the University, such as the Wellcome Centre for Molecular Parasitology, the MRC-University of Glasgow Centre for Virus Research and the Wolfson Wohl Cancer Research Centre, whose scientists do ground-breaking research employing bioinformatic approaches in the study of disease.

Information for international students

International English Language Testing System (IELTS) Academic and Academic Online (not General Training)

• 6.5 overall with no subtest less than 6.0

• IELTS One Skill Retake Accepted

• Tests must have been taken within 2 years 5 months of programme start date. Applicants must meet the overall and subtest requirements using a single test.