• Postgraduate

Bioinformatics MSc

Register for open day
Register for open day
Overview

Overview

Our Bioinformatics Masters bridges the interfaces between genomics, computing and healthcare and aims to equip you with the skills to analyse, interpret and use biological data to inform and improve healthcare and health outcomes.

You will consider biological data generated by technologies such as genome and next-generation sequencing and microarray expression technology.

Additionally, you will also learn how the results of analysis can be applied to improve health outcomes.

Throughout your studies, you will be encouraged to reflect on the ethical, legal and social implications of using genomics data.

Blood sample in test tube on a sheet of DNA code

Select your desired study option, then pick a start date to see relevant course information:

Study options:
We support flexible study by offering some of our courses part-time or via distance learning. To give you real world experience before you graduate, we also offer some courses with a placement or internship. All available options are listed here. Your choices may affect some details of your course, such as the duration and cost per year. Please re-check the details on this page if you change your selection.

Start date:

If your desired start date is not available, try selecting a different study option.

Why study Bioinformatics with us?

Why study Bioinformatics with us?

A collage of students

What our students say…

The University is very modern, and it has a really good atmosphere. 

Costel Cantia
Next
Graphic announcing UWL's New School of Medicine and Biosciences
Industry focused teaching
Bridging the gap between genomics, computing and healthcare.
Lifelong careers support from the UWL Careers Service.
Course detail & modules

Course detail & modules

We welcome students and professionals from a range of academic and work backgrounds, including:

  • biomedical sciences
  • forensic science
  • nursing 
  • public health
  • psychology
  • healthcare science
  • pharmaceutical.

The course covers core principles, as well as statistical, computing and knowledge management skills.

In addition, it will equip you with the technical ability you need to analyse genetics and genomics data and the underlying health associations between gene variants, disease susceptibility and drug response.

In the Bioinformatics and Advanced Bioinformatics modules you will work in interdisciplinary teams as much as possible. Together, and individually, you will:

  • undertake core practice in sequence and structure analysis techniques and provide you with a strong foundation in omics and NGS analysis. R, Python, Linux, and the user-friendly Chipster software provided by ELIXIR-Finland at CSC are used in the NGS exercises
  • problem-solve in real healthcare or industry scenarios using bioinformatics and computational analysis 
  • learn research design and methodologies in bioinformatics 
  • apply your understanding of genetic variation to disease modelling
  • develop an analysis strategy for a new service that builds on your knowledge of genomics, bioinformatics and programming 
  • apply the relevant statistical and analytical methods to generate new information.

You will learn from experts in computing, healthcare, mathematics and statistics, whose current practice and research will enhance your postgraduate experience.

You will study all compulsory modules and may choose TWO out of five optional modules listed.

Compulsory modules

  • Introduction to Genetics and Genomics

    During this module you will develop an understanding of the key areas of genomics, human genetics and genetic variation. You will also examine the genomics basis of diseases and how it can be used to improve health outcomes.

  • Bioinformatics and Functional Genomics

    On this module you will be introduced to basic practical sequence and structure analysis techniques, tools and resources. You will also develop a strong foundation in 'omics and NGS analyses. There will be opportunities for you to apply bioinformatics and computational analysis to problem-solving in real healthcare or industry scenarios.

  • Data Science for Bioinformatics

    On this module you will be introduced to data science in bioinformatics. You'll have opportunities to gain practical skills for programming such as Python and R. You will also be able to apply statistical and modelling techniques to explore big data, and design appropriate database and web solutions for computational biology and bioinformatics data storage, visualisation or dissemination.

  • Advanced Bioinformatics and Genome Analysis

    This module will help you to develop knowledge and skills that underpin the clinical application of bioinformatics. The module will build on your genomics, bioinformatics and programming knowledge to develop an analysis strategy for a new service. There will also be opportunities for effective interdisciplinary team working.

  • Bioinformatics Project

    This module will give you the chance to demonstrate your ability to organise and carry out a major piece of work. You will gather background information and research the literature and data . You will also design and execute a research plan to solve a bioinformatics problem, and discuss existing results and present your new findings through a series of written and oral presentations.

Optional modules

  • Machine Learning

    Machine learning is an application of artificial intelligence that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed.

    This module familiarises you with some basic machine learning algorithms and techniques and their applications, as well as general questions related to analysing and handling large data sets. Several software libraries and data sets publicly available will be used to illustrate the application of these algorithms. The emphasis will be thus on machine learning algorithms and applications, with some broad explanation of the underlying principles.

  • Information Systems in Healthcare

  • Data Management in Healthcare

    Data is revolutionising healthcare. The benefits of data when correctly used extend to patients, providers and board members, and the technology can make centralised patient management a reality. The aim of this module is to give you the knowledge and hands-on experience of developments in the broad range of data-driven healthcare.

  • Data Architecture and Security

  • Big Data Analytics

    Big data is a fast-growing field and skills in the area are some of the most in-demand today. Big data technologies cover a range of architectures, frameworks and algorithms designed to handle very large and often highly complex datasets.

    The module will enable you to understand big data, its applications and associated issues for storing, managing, processing and analysing massive amounts of datasets, as well as become familiar with software tools and frameworks underpinning big data analytics.

    You will also acquire the knowledge of statistical, mathematical and machine-learning techniques, and develop the ability to design and implement big data analytics modelling and applications to real-world problems.

Entry requirements

Entry requirements

You should have an honours degree (2:2 or above) in a health-related subject including:

  •  healthcare science
  •  forensic science
  •  biology
  •  physics
  •  chemistry
  •  pharmacology
  •  statistics
  •  computing 
  •  medicine
  •  nursing
  •  podiatry
  •  physiotherapy
  •  psychology
  •  pathology

You will be required to attend an interview. You will need to provide evidence of your achievements, for example:

  • a relevant professional qualification at a suitable level, and/or
  • several years' relevant post-qualifying professional experience.

If you do not meet the entry criteria to study this course but you have relevant experience, you are still welcome to apply. Your application will be considered on an individual basis.

We look for students who show enthusiasm and a passion for the subject through previous study or professional experience. If you have any questions about the relevance of your qualifications or experience please contact the course leader shown in the teaching staff.

6.5 IELTS or above

You need to meet our English language requirement of 6.5 overall score for IELTS, with a minimum of 5.5 for each of the 4 individual components (Reading, Writing, Speaking and Listening). Visit our English language requirements page for information on other English language tests we accept.

You also need academic qualifications at the same level as UK applicants. In some countries where teaching is in English, we may accept local qualifications. Check for local equivalents.

We offer pre-sessional English language courses if you do not meet these requirements. Find out more about our English Language courses.

You will be required to attend an interview. You will need to provide evidence of your achievements, for example:

  • a relevant professional qualification at a suitable level, and/or
  • several years' relevant post-qualifying professional experience.

If you do not meet the entry criteria to study this course but you have relevant experience, you are still welcome to apply. Your application will be considered on an individual basis.

We look for students who show enthusiasm and a passion for the subject through previous study or professional experience. If you have any questions about the relevance of your qualifications or experience please contact the course leader shown in the teaching staff.

Fees & funding

Fees & funding

{{ formatCurrencyValue(currentVariantData.field_p_cv_uk_eu_main_fee.name) }} per year

Please note:

  • Fees for the 2026/27 academic year and onwards may be subject to Government regulation and change.
  • Tuition fees are charged for each year of your course. If your course runs for two years or more, you will need to pay the fee for each academic year at the start of that year.
  • If your course runs for less than two years, the cost above is for your full course and you will need to pay the full fee upfront.
  • If no fee is shown above then the fees for this course are not available yet. Please check again later for updates.

Funding your studies

If you are studying a Masters course you may be eligible to apply for a Postgraduate Loan, this may help contribute towards your course fees and living costs.

Additional funding is available to some types of students, such as disabled students or those with dependants.

We offer a range of scholarships and bursaries, including awards for specific subjects.

Awards for human and social science students are also on offer.

View full details, including conditions and eligibility.

Help with funding
{{ formatCurrencyValue(currentVariantData.field_p_cv_int_main_fee.name) }} per year

Please note:

  • Fees for the 2026/27 academic year and onwards may be subject to Government regulation and change.
  • Tuition fees are charged for each year of your course. If your course runs for two years or more, you will need to pay the fee for each academic year at the start of that year.
  • If your course runs for less than two years, the cost above is for your full course and you will need to pay the full fee upfront.
  • If no fee is shown above then the fees for this course are not available yet. Please check again later for updates.

International students - funding your studies

We offer scholarships for international students including International Ambassador Scholarships. 

Further information about funding and financial support for international students is available from the UK Council for International Student Affairs.

 

Financial support for international students
Teaching staff

Teaching staff

Shanyu Tang

Professor Shanyu Tang

Shanyu Tang is Professor of Information Security at the University of West London, having joined academia in 2000 as a Lecturer in Informatics and Multimedia Technology in the School of Informatics and Multimedia Technology at the University of North London, United Kingdom. He is a Fellow of the British Computer Society (FBCS) and a Fellow of the Higher Education Academy (FHEA).

He is the lead/corresponding author of 106 scientific publications: 66 peer-reviewed journal papers, including IEEE/ACM Transactions, IET journals and IEEE Journal of Biomedical and Health Informatics, 38 conference papers and two books. He, as a principal investigator, is a recipient of 11 external research grants, including seven national research grants. He filed an Internet of Things security patent.

As first supervisor, he has successfully supervised to completion nine PhDs in computer science and informatics and has been involved in seven external PhD examinations. He is on editorial boards of international journals in computer science and informatics.

He was a scientific adviser to several universities and organisations, sitting on the university’s research committee from 2007 to 2017 and the IEEE Admission and Advancement Committee Panel 2011. He chaired international conferences, served on conference program committees and gave numerous invited research seminars.

His research interests include bioinformatics, health data security, secure communication and social media analytics, most notably the use of machine learning and chaos theory to these areas.

He has supervised five PhDs in Information Security to completion and has been involved in seven external PhD examinations.

Shanyu Tang is Professor of Information Security at the University of West London, having joined academia in 2000 as a Lecturer in Informatics and Multimedia Technology in the School of Informatics and Multimedia Technology at the University of North London, United Kingdom. He is a Fellow of the British Computer Society (FBCS) and a Fellow of the Higher Education Academy (FHEA).

He is the lead/corresponding author of 106 scientific publications: 66 peer-reviewed journal papers, including IEEE/ACM Transactions, IET journals and IEEE Journal of Biomedical and Health Informatics, 38 conference papers and two books. He, as a principal investigator, is a recipient of 11 external research grants, including seven national research grants. He filed an Internet of Things security patent.

As first supervisor, he has successfully supervised to completion nine PhDs in computer science and informatics and has been involved in seven external PhD examinations. He is on editorial boards of international journals in computer science and informatics.

He was a scientific adviser to several universities and organisations, sitting on the university’s research committee from 2007 to 2017 and the IEEE Admission and Advancement Committee Panel 2011. He chaired international conferences, served on conference program committees and gave numerous invited research seminars.

His research interests include bioinformatics, health data security, secure communication and social media analytics, most notably the use of machine learning and chaos theory to these areas.

He has supervised five PhDs in Information Security to completion and has been involved in seven external PhD examinations.
Study & career progression

Study & career progression

A man looking at a graph on a laptop with a man in scrubs testing substances in the background

Once you graduate you could go on to work in:

  • clinical informatics
  • pharmaceutical and biotech industries
  • personalised medicine and wellbeing
  • agricultural science and research
  • animal research 
  • academic research 
  • the food industry
  • public institutions
  • public health
  • IT.

You may also want to explore a related area of study. Please see our full list of courses for further information.

How to apply

How to apply

Search for courses

Important notes for applicants

Disclaimer

*Modern universities - defined as higher education institutions that were granted university status in, and subsequent to, 1992.

**The National Student Survey 2023 and 2024 - Average of answers to all questions by registered student population. Excludes specialist institutions.

Testimonials - our students or former students provided all of our testimonials - often a student from the course but sometimes another student. For example, the testimonial often comes from another UWL student when the course is new.

Optional modules - where optional modules are offered they will run subject to staff availability and viable student numbers opting to take the module.

Videos - all videos on our course pages were accurate at the time of filming. In some cases a new Course Leader has joined the University since the video was filmed.

Availability of placements - if you choose a course with placement/internship route we would like to advise you that if a placement/internship opportunity does not arise when you are expected to undertake the placement then the University will automatically transfer you to the non-internship route, this is to ensure you are still successful in being awarded a degree.