Postgraduate study
Life & Physical Sciences

MSc Bioinformatics*

As biological sciences have become more data driven, bioinformatics is now central to modern biological research, from genetics, nutrition and epidemiology to ecology, neuroscience and biomedicine.

Course information

Full-time

  • September enrolment: 1 year, January enrolment: 16 months, including a summer break

More full-time details

2019 entry

Part-time

  • September enrolment: 2 years, including a summer break, January enrolment: 28 months, including two summer breaks

More part-time details

2019 entry

Contact details

Further information

 

This programme teaches you how to manage and manipulate large datasets to reveal new insights in biological sciences. You get intensive training in a computer-based approach to biological research. You develop the computational and analytical understanding necessary as a platform for processing biological data. This involves the appreciation of biochemistry and molecular biology, together with IT and specialist skills in computer programming, data analysis, statistics and computational biology for multidisciplinary careers in research.

This course is delivered at Teesside University National Horizon Centre, at its Darlington Campus. The National Horizons Centre is a new £22m biological research, teaching and training facility, due to open in March 2019, which aims to address the growth needs of the emerging bio-based industries set to transform the UK economy, including biologics, industrial biotechnology and bio-pharmaceuticals.

The majority of modules for this master’s course are taught at the new National Horizons Centre at the University’s Darlington campus. This £22m purpose-built biosciences research, education and training facility is a focal point for the growing regional biosciences community.

For an MSc award you must successfully complete 120 credits of taught modules and a 60-credit master's research project.

Course structure

Core modules

Advanced Data Analytics

This module provides you with the core principles and practical skills to apply state-of-the-art computational methods to perform data analytics. The skills are very important in the new horizon of data analysis where existing massive amount of data contains valuable knowledge, which is critical for prediction and decision-making. Due to its characters (3V: volume, velocity, and variety), computational methods are required to extract such knowledge.

You form a solid foundation of 1) predictive analytics, 2) data-driven decision making which refers to tools and techniques for building statistical or machine learning models to make predictions and decisions based on data. Practical guidance about how to handle unlabelled, noisy, incomplete, large-scale data is discussed and you learn how to select the best technique to handle different type of data in different scenarios.

Bioinformatic Techniques

Genomics and Bioinformatics

You gain an in depth understanding of advances genomics, proteomics and bioinformatics knowledge and their applications in specific disease state. You learn about the most recent technologies including next generation gene sequencing, genome editing, genomic and bioinformatics analyses. This module also explores the genomic application for disease treatment and prevention (pharmacogenomics), personalised medicine as well as ethical challenges in this field.

Omics and Systems Approaches in Biology

You gain an extensive, critical and integrative understanding of how modern ‘omics’ analysis approaches are used to make inferences about biological functions. ‘Omics’ includes genomics, transcriptomics, proteomics, and metabolomics. In addition, you gain a detailed overview of the use of ‘omics’ data in analysis at a systems level - systems biology - and of the relationship between protein structure analysis and the proteome. You cover experimental design and the practicalities of analysing large ‘omics’ datasets. You will put these analysis concepts into practice during extensive computer lab practicals.

Programming

This module introduces programming, data types, use of algorithms involving repetition and conditional execution. Through a series of problem solving computer lab practicals you will explore the development of well-structured programs and data structures, with attention to maintainable, robust, reliable, and reusable code, and thorough testing.

Research Project

Investigate an area of engineering or science for an extended period through a research project or design project, working independently at a level recognised as at the forefront of the discipline. You develop key research skills, applying and creating your knowledge through keynote lectures and self-managed independent study. You will demonstrate your capacity for comprehensive and objective analysis, and for developing innovative and constructive proposals as a solution to the project topic. We support you through tutorials and/or one-to-one guidance but you require a high degree of autonomy.

 

Optional modules

Pathobiology of Genetic Disorders and Neurodegenerative Disease

You explore the pathophysiological basis of diseases commonly associated with the central nervous system, including Alzheimer’s disease, Parkinson’s disease, epilepsy and stroke. The module will explore the genetic, molecular, cellular and neurochemical pathways involved in diseases of the central nervous system and how such abnormalities manifest clinically. It will also examine the various treatment strategies available for such diseases.

Pathobiology of Infectious Diseases

You gain a deep understanding of infectious disease and will cover a wide range of medically-important human pathogens. Key aspects of pathobiology will be taught including pathogen genomics and evolution, bioinformatics, and the cellular and molecular biology that underpin these host pathogen interactions. Subversion of key mammalian cell biological processes, including immunology, that are targeted by pathogens will also be described. Advanced laboratory techniques and bioinformatics will be introduced that are commonly used to uncover mechanisms of pathogenesis.

 

Modules offered may vary.

How you learn

Making the transition to postgraduate-level study can be challenging. Support with making this transition is seen as an important element of this programme.

The Data Analytics and Algorithms for Bioinformatics and Database Theory and Application modules help you understand the requirements of academic study at postgraduate level, to enhance your skills in academic writing and referencing, and to help you develop the skills necessary to operate professionally and ethically in planning and implementing a master’s-level research project.
By including work-based problem-solving projects and case study exercises this programme emphasises real-world working. This helps to develop your critical thinking skills as well as your ability to design, execute and present findings of research, allowing you to cultivate the skills employers are seeking to set you on a successful career path.

A significant feature of the programme is the opportunity to gain experience of working in state-of-the-art bioinformatics research facilities within the National Horizon Centre.

How you are assessed

You are assessed on subject knowledge, independent thought and skills acquisition through formative and summative assessment. 

Modules are assessed by a variety of methods including examination and in-course assessment with some utilising other approaches such as, oral presentations, technical interviews and technical reports alongside literature surveys, evaluations and summaries.

You are presented with an assessment schedule providing details of the submission deadlines for summative assessments.

Work placement

There may be short-term placement opportunities, particularly during the project phase of the course.

Career opportunities

Our bioinformatics programme equips you with a strong foundation for further PhD research or for prospective employment. There is an increasing demand for bioinformatics skills across the biotechnology, life sciences and pharmaceutical sectors. The ability to manage, analyse, integrate and visualise big data using technologies such as Python and R is also applicable to fields including software development, data analytics and finance.

Entry requirements

Applicants are normally expected to have at least a UK 2.2 honours degree, or equivalent, in a subject related to science, engineering or technology. 

In addition, international students normally need at least a 6.0, with no component below 5.5, in the International Language Testing System (IELTS) test.

If your first degree is not in one of the subject areas listed above please contact our admissions team for guidance and advice on how you might become eligible. We may be able to offer you alternative access routes.

For additional information please see the entry requirements in our admissions section

International applicants can find out what qualifications they need by visiting Your Country

* Subject to University approval

Course information

Full-time

  • September enrolment: 1 year, January enrolment: 16 months, including a summer break

More full-time details

2019 entry

Part-time

  • September enrolment: 2 years, including a summer break, January enrolment: 28 months, including two summer breaks

More part-time details

2019 entry

Contact details

Further information