MSc ( 1 year Full-time / 2 years Part-time )


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. This programme will teach you how to manage and manipulate large datasets to reveal new insights in biological sciences.  You will get intensive training in a computer-based approach to biological research, with the opportunity to develop specialist skills in computer programming, data analysis, statistics and computational biology.

New analytical techniques deliver ever more data about genes, proteins, metabolites and the interactions between them. Bioinformatics is the discipline tasked with turning all this data into useful information and new biological knowledge. With applications spanning the breadth of life science disciplines, there is now high demand for trained bioinformaticians.

Prior experience of computer programming is not required as you will be taught the latest tools and techniques in bioinformatics, which you will then apply to your own research project.  You will also collaborate with peers to build new bioinformatics solutions to real-world problems as part of an innovative group project. 

This programme is delivered by academics who are actively engaged in developing bioinformatics tools and applying them in areas such as genome sequencing, proteomics, evolution, ecology, psychology, cancer, diabetes and other diseases. We have an extensive network of academic and industrial collaborators around the UK and in Europe, who contribute to teaching, co-supervise projects and provide employment opportunities.


  • Training to manage, analyse, integrate and visualise big data using technologies such as Python and R
  • Development of skills applicable to software development, data analytics and finance
  • Delivered by academics who are actively engaged in developing bioinformatics tools and applying them in areas such as genome sequencing, proteomics, evolution, ecology, psychology, cancer, diabetes and other diseases
  • Opportunities to publish scientific papers (recent graduate had her MSc project work included in a paper published in Science)
  • Strong foundation for employment in biotechnology, life sciences and pharmaceutical sectors or PhD research

Student Experience

We spoke to Raphaella Jackson, who is currently undertaking a Bioinformatics MSc at Queen Mary University of London’s School of Biological and Chemical Sciences (SBCS). She is a citizen of three countries – Canada, United States and New Zealand and spoke about her experience of the course - Read more

Research and teaching 

By choosing to study at a Russell Group university you will have access to excellent teaching and leading research. Our staff draw heavily upon their industrial or research council-funded research to inform their teaching and ensure projects are topical and well-resourced.

Developing bioinformatics has allowed me to work in one of the best companies when it comes to smart science. They help me understand our customers’ needs as they seek to implement bioinformatics pipelines to extract new knowledge from the data generated by our sequencers
Yasmine (Bioinformatics 2016 graduate, currently working at Illumina)

Informal enquiries 

If you have questions about this programme which you would like to put to Professor Conrad Bessant, Professor of Bioinformatics and Bioinformatics MSc Programme Director, please contact:

Tel: +44(0)207 882 6510


Prior experience of computer programming is not required as you will be taught the latest tools and techniques in bioinformatics, which you will then apply to your own research project. You will also work collaboratively to build new bioinformatics solutions to real-world problems as part of an innovative group project.

If you have any questions about the content or structure, contact the programme director Professor Conrad Bessant

Taught modules

Your taught modules take place in blocks of two weeks of full-time teaching (normally 9am-5pm), followed by weeklong study breaks for independent learning and coursework. This structure  allows for an intensive learning experience, giving students the opportunity to immerse themselves in their subject. You will also benefit from small group teaching; for example, seminar groups for 2017-18 were all around 20 students. 

The following intensive taught modules run in the autumn term:

  • Genome Bioinformatics: This module provides an introduction to bioinformatics, focusing specifically on the analysis of DNA sequence data. Lectures cover the bioinformatics methods, algorithms and resources used for tasks such as sequence assembly, gene finding and genome annotation, phylogenetics, analysis of genomic variance among populations, genome wide association studies and prediction of gene structure and function. Practical exercises are used to gain experience with relevant existing bioinformatics tools, data formats and databases.
  • Coding for Scientists: This module provides a hands-on introduction to computer programming (popularly known as coding) using scripting languages popular in the field. The focus is on producing robust software for repeatable data-centric scientific work. Key programming concepts are introduced, and these concepts are then brought together in scientifically relevant applications to analyse data, interact with a database and create dynamic web content. Good coding practice, such as the importance of documentation and version control, is emphasised throughout.
  • Statistics and Bioinformatics: This module is focussed on teaching data analysis using the statistical programming language R. The module covers the basics of using R; drawing publication-standard graphs with R; experimental design; exploratory data analysis; the fundamentals of statistical testing including t-tests and chi-square tests; ANOVA and Regression; fitting and interpreting general linear models; the basics of bioinformatic analysis in R. The module is taught with a mix of theory and practice, with a typical day including roughly two hours of theory instruction in the morning followed by a practical session in the afternoon, often involving hands-on analysis of real experimental data sets.
  • Post-genomic Bioinformatics: This module provides an introduction to bioinformatics, focusing specifically on the management and analysis of data produced by so-called post-genomic methods such as transcriptomics, proteomics and metabolomics. Lectures cover the bioinformatics methods, algorithms and resources used for tasks such as the identification and quantitation of transcripts, proteins and metabolites, and analysis of the interactions between these key biological molecules. Practical exercises are used to gain experience with bioinformatics tools, data formats and databases that have been developed for this field.

Group project

After Christmas you will spend six intensive weeks working on a group project where skills developed in previous modules are applied to develop a novel piece of software to meet a real biological need. Additional skills you can pick up during this module include web development, database design and collaborative working using GitHub.

Research project

You then embark on an individual six month research project, the topic of which we are reasonable flexible about as long as it has bioinformatics at its core. We offer a list of projects supervised by members of Queen Mary, but you can also propose your own projects, which may be carried out elsewhere (e.g. at your employer if you are a part time student).

Recent dissertation topics include:

  • Understanding genetic factors involved in addiction and mental health
  • Comparative genomics & molecular evolution
  • Early diagnosis of breast cancer
  • Genomic degradation in the model system of cardiocondyla ants and their endosymbiotic bacteria
  • Uncover microbial diversity across the ants
  • Microbial diversity in the deep biosphere
  • Structural alteration in colorectal cancer genomes
  • Detecting fatigue during cognitively demanding tasks using EEG and machine learning
  • Clinical utility of normal appearing tissues adjacent to tumour in breast cancer
  • Understanding cell type: a big data question
  • Unravelling the aetiology of tendinopathy
  • In silico estimation of tissue-infiltrating immune and stromal cell mixture and abundance in pancreatic cancer microenvironment
  • An RNAseq analysis of the role of EphrinB2 in Craniopharyngioma

Study part-time

Our Bioinformatics MSc is currently available for one year’s full-time study, or to study part-time over two years.

Entry requirements

A minimum of an upper second-class BSc (Hons) degree (or equivalent international qualification) in biology or other relevant natural sciences subject.

Applicants with a good lower second class degree may be considered on an individual basis, taking into account relevant background and related achievements.

English language requirements

All international students are required to provide evidence of their ability in English language.

The minimum level required for entry to our postgraduate programmes is:

  • IELTS: 6.5 overall including 6.0 in Writing and 5.5 in Reading, Listening and Speaking
  • TOEFL: 92 overall including 21 in Writing, 18 in Reading, 17 in Listening and 20 in Speaking
  • PTE Academic: 62 overall including 57 in Writing and 51 in Reading, Listening and Speaking
  • Trinity ISE: Trinity ISE II with a Distinction in Writing, Reading, Listening and Speaking, or Trinity ISE III with a minimum of Pass in Writing, Reading, Listening and Speaking
  • C2 Cambridge English: Proficiency (CPE): 176 overall including 169 in Writing, and 162 in Reading, Listening and Speaking
  • C1 Cambridge English: Advanced (CAE): 176 overall including 169 in Writing, and 162 in Reading, Listening and Speaking  

For further information about our English language requirements please visit the QMUL international pages.

Am I eligible?

To check your eligibility contact our Postgraduate Admissions team:

Tel: +44 (0)20 7882 3328

Learning and teaching

Our Bioinformatics programme combines traditional lectures and hands-on practical computer sessions. Group work, student presentations and open discussion are an integral part of the programme, giving you the chance to develop communication and team-working skills. We take pride in cultivating a close-knit and friendly working relationship between academics and students on this programme.  You will benefit from small group teaching, normally typically around 20 students in each seminar, allowing for a more intensive learning experience and increased interaction.

Taught modules

Your taught modules take place in blocks of two weeks of full-time teaching (normally 9am-5pm), followed by weeklong study breaks for independent learning and coursework. Most modules are taught through lectures during the morning, with practicals, seminars, discussion groups and workshops taking place in the afternoon. 


The QMUL MSc Bioinformatics programme is taught by experts who are all actively involved in cutting edge computational biology research.

The MSc is led by Prof Conrad Bessant, who has over 20 years' experience in the development of novel methods for analysing biological data. He has been teaching bioinformatics at Masters level since 2002 and is lead author of the textbook “Building Bioinformatics Solutions”, published by Oxford University Press. The genome bioinformatics module is led by Dr Yannick Wurm, an expert in handling next generation sequencing data, and a world leader in the evolutionary genomics of social insects, e.g. ants and bees. Dr Wurm is also at the forefront of developing new bioinformatics software.

Dr Fabrizio Smeraldi leads the coding module, and co-leads the group project with Prof Bessant. He has extensive experience in machine learning. His research includes automated determination of behavioral phenotype from video, and novel sequence analysis algorithms.  The statistics module is taught by Dr Rob Knell, a Reader in ecology and evolution with a deep understanding of how statistical methods can be applied to answer biological problems. His is an expert in the R platform for statistical computing, and author of the popular ebook “Introductory R: A Beginner's Guide to Data Visualisation, Statistical Analysis and Programming”.

Other leading academics contribute to the taught modules or supervise projects. These include Prof Claude Chelala and Dr Pedro Cutillas from Barts Cancer Institute, Dr Rob Lowe and Dr Miguel Branco from the Blizard Institute, and Dr Michael Barnes from the William Harvey Research Institute.


You are assessed primarily by coursework, with a small number of in-class assessments. Coursework is usually in the form of a biological problem that for which a bioinformatics must be devised, implemented and written up. You also undertake an individual project assessed by a 10,000-word dissertation and a presentation that is given on the final day of the course.


Tuition fees for Home and EU students

2020/21 Academic Year

Full time £12,950
Part time £6,500

Tuition fees for International students

2020/21 Academic Year

Full time £23,950
Part time £12,000

Part time fees are charged per annum over two years for a two year programme and per annum over three years for a three year programme. A percentage increase may be applied to the fees in years two and three.

This increase is defined each year and published on the intranet and in the Tuition Fee Regulations. A 3% increase was applied to the unregulated university fees in 2019/20. Further information can be viewed on our University Fees webpage, including details about annual increases.


There are a number of sources of funding available for Masters students.

These include a significant package of competitive Queen Mary University of London (QMUL) bursaries and scholarships in a range of subject areas, as well as external sources of funding.

Queen Mary bursaries and scholarships

We offer a range of bursaries and scholarships for Masters students including competitive scholarships, bursaries and awards, some of which are for applicants studying specific subjects.

Find out more about QMUL bursaries and scholarships.

Alternative sources of funding

Home/EU students can apply for a range of other funding, such as Professional and Career Development Loans, and Employer Sponsorship, depending on their circumstances and the specific programme of study.

Overseas students may be eligible to apply for a range of external scholarships and we also provide information about relevant funding providers in your home country on our country web pages.

Download our Postgraduate Funding Guide for detailed information about postgraduate funding options for Home/EU students.

Read more about alternative sources of funding for Home/EU students and for Overseas students.

Tel: +44 (0)20 7882 5079

Other financial help on offer at Queen Mary

We offer one to one specialist support on all financial and welfare issues through our Advice and Counselling Service, which you can access as soon as you have applied for a place at Queen Mary.

Our Advice and Counselling Service also has lots of Student Advice Guides on all aspects of finance including:

Tel: +44 (0)20 7882 8717

Graduate employment

Our Bioinformatics programme will equip 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.

What are our graduates doing now?

The range of skills gained through our Masters programmes, coupled with opportunities for extra-curricular activities, has enabled recent Bioinformatics students to enter careers such as:

  • Software Engineer/Bioinformatician at European Bioinformatics Institute
  • Informatics Assistant at Blizard Institute
  • PhD Student at Queen Mary University of London
  • Bioinformatics PhD Researcher at UCL Cancer Institute

Careers support at QMUL

Throughout the course, postgraduates have access to a careers programme to prepare them for applying for work after graduation. This programme includes workshops on job hunting and job applications as well as employer events to facilitate networks and help students to explore their options. Recent career events open to the School’s postgraduates include the SBCS Industrial Liaison Forum featuring small and medium sized employers, and workshops on applying for and doing a PhD.

Queen Mary’s location between Canary Wharf, the City and the Olympic Village redevelopment means that there are substantial opportunities for on campus and local part time work and work experience. On campus there are 1200 job and volunteer opportunities ranging from E-learning Assistant to Website Administrator and from Society President to Student Mentor. QTemps job agency offers work suitable for current students and recent graduates, QMSU Volunteering facilitates volunteering and QM JobOnline hosts over 800 part time and full time job vacancies.

  • Read more about our careers programmes and range of work experience opportunities on the QM Careers pages.


Nazrath Nawaz – MSc Bioinformatics (graduated 2016)

Now PhD student in Computational Biology at Queen Mary University of London

I obtained my BSc in Medical Genetics at Queen Mary which gave me a firm biological background. The rapid expansion of big data within Biology as well as finding a passion for the theoretical side lead me to choose to do an MSc in Bioinformatics. This intensive one-year degree allowed me to completely shift from the wet lab to a data scientist. Through the courses offered, we were taught to code in various relevant programming languages and thus gained the necessary skills to analyse data. With my background knowledge and the newly acquired skill set, I was equipped to pursue a PhD in Computational Biology. Even though I have chosen a route in academia, the programming skills and expertise of the MSc can be applied to handle any type of data, including industry. Completing this MSc helped to open up my career options and allowed me to choose what I really wanted to do. By the time I complete my PhD next year, I will have been at Queen Mary for eight years and have thoroughly enjoyed my time here. I have met and worked alongside some of the most amazing individuals and leading pioneers in their respective fields. Queen Mary has become my home.


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