The first of its kind in the UK, this MSc is highly regarded by employers for its real-world relevance and applied content. The course aims to develop advanced theoretical knowledge and computational skills and apply them to help solve real-life biological problems. This MSc is recognised by the BBSRC.

Applied Bio

At a glance

  • Start dateFull-time: October. Part-time: throughout the year
  • DurationOne year full-time; two-three years part-time
  • DeliveryTaught Modules 40%, Group Project 20%, Individual Research Project 40%
  • QualificationMSc
  • Study typeFull-time / Part-time

Who is it for?

This course aims to equip graduate scientists with the computational skills and awareness needed to archive, analyse and interpret the vast amounts of biological data now becoming available. On completion of this course, you will be able to apply information technology to the development of new drugs and diagnostic tools.

Additionally, you will gain the skills to design and implement new tools and software plugins to fulfil the need of the research community, and will be equipped with a diverse set of knowledge and skills that directly meet the requirements of employers in this sector.

Why this course?

This new and fast-growing field requires forward-thinking people who understand both the biological and computing aspects of this science – this MSc has been specifically designed to produce graduates of this nature.

Our students come from the UK and a combination of European and International countries. You will therefore experience working closely with people from different cultures and backgrounds – essential skills for your future career.

Class sizes are kept relatively small to help create an interactive environment and to ensure each student receives excellent support from our academic team.

Informed by Industry

Cranfield University benefits from the input of a group of world-renowned experts in a range of applied sciences including bioinformatics. We lead and collaborate in diverse research and consultancy projects, both nationally and internationally.

Our collaborators include:

  • GlaxoSmithKline
  • Unilever
  • Sanofi Aventis
  • Rothamsted Research
  • The European Bioinformatics Institute
  • London School of Hygiene and Tropical Medicine
  • University of Athens
  • Cambridge University.

Your teaching team

You will be taught by an expert multidisciplinary team both from Cranfield University and externally:

Course details

The taught programme is generally delivered from October until March and is comprised of eight compulsory taught modules, a group project and an individual thesis project. Students on the part-time programme will complete all of the compulsory modules based on a flexible schedule that will be agreed with the Course Director.

Group project

Real-life experience

Working in project teams is part of everyday working life. It requires not only your individual expertise but also an appreciation of the skills of the other members of the team. This part of the course gives you the opportunity of working as part of a team on a group project. This is an invaluable experience that will help you to recognise and implement the differing contributions that colleagues bring to team work, and the different roles that we can choose to play within a team. 

Diverse study environment

agrifood

Individual project

Industry related projects

A four-month thesis project carried out either at Cranfield or an external research establishment or commercial organisation within the UK or Europe. This gives you the chance to concentrate on a subject area of particular interest to you, perhaps in collaboration with the type of organisation that you are hoping to find employment with.

Real-life-problems solving thesis projects

Our MSc students finalise their hands-on study practice with individual thesis projects that solve problems in multidisciplinary areas whilst working under academic supervision. Some recent projects include:

  • Development of a Web-based resource for tuberculosis genotyping and diagnosis from whole genome sequencing data: PhyTB.

This project by Ernest Diez (2013-2014) is focused on creating PhyTB - an application for the interactive study of variation in M.tuberculosis using data from the PhyloTrack library.

Visit project page

Further reading

  • Applications of data science and machine learning in detection of meat adulteration.

This project by MSc student Rafal Kural (2014-2015) is focused on the application of machine learning methods to unravel hidden patterns of meat samples using Fourier Transform Spectrometry, Gas Chromatography Mass Spectrometry, High Performance Liquid Chromatography and VideometerLab. Over the course of this work it has been proven that it is certainly possible to obtain very accurate detection of meat adulteration, reaching sample adulteration level prediction accuracy of 100% for GCMS and 90-97% for FTIR and VM data.

Assessment

Taught Modules 40%, Group Project 20%, Individual Research Project 40%

University Disclaimer

Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the core modules and some optional modules affiliated with this programme which ran in the academic year 2017–2018. There is no guarantee that these modules will run for 2018 entry. All modules are subject to change depending on your year of entry.

Compulsory modules
All the modules in the following list need to be taken as part of this course

Introduction to Bioinformatics using Perl

Module Leader
  • Dr Fady Mohareb
Aim

    To provide an overview of bioinformatics, and to introduce the most relevant concepts in IT, as well as providing students with the ability to program in PERL; the most popular programming language in the bioinformatics community.

    Teaching team includes: Tomasz Kurowski

Syllabus
    Introduction to bioinformatics, algorithms & programming, Introduction to PERL programming for: data manipulation, file maintenance, pipelining, packaging and interfacing system facilities.
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Retrieve relevant nucleotide, protein sequences and their corresponding metadata from online public data resources
  • Access remote Linux-based HPC and apply commonly used terminal commands
  • Develop simple Perl scripts for sequence manipulation
  • Develop advanced stand-alone Perl programs for the acquisition and consolidation of data from remote databases

Exploratory Data Analysis and Essential Statistics using R

Module Leader
  • Dr Fady Mohareb
Aim

    To provide an overview of important concepts in statistics and exploratory data analysis. The module introduces the main concepts in analysing biological datasets using the R environment, as well as developing bespoke scripts for multivariate analysis such as principal components analysis and hierarchical clustering.

    Teaching team includes: Dr Michael Cauchi, Dr Chris Walton and Dr Maria Anastasiadi.


Syllabus
    Introductory, descriptive and inferential statistics, significance testing, exploratory data analysis (PCA, HCA), introduction to programming using R.
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Devise basic R programs to meet given specifications
  • Apply different statistical techniques and be able to implement them programmatically in R
  • Effectively integrate and devise statistical methods into experimental protocol design

Next Generation Sequencing Informatics

Module Leader
  • Dr Fady Mohareb
Aim

    To introduce the techniques that have given rise to the genomic data now available, and develop skills and understanding in the bioinformatics approaches that facilitate evaluation and application of these data, which has been a huge stimulus for a lot of breakthrough discoveries in biology.

    Teaching team includes: Dr Robert King, Tomasz Kurowski, Prof Andrew Thompson and Dr Zoltan Kevei. 


Syllabus
    NGS raw reads pre-processing and quality control, hands-on computer practicals using popular tools for genome analysis, RNA-Seq transcriptome profiling, SNP calling and genotyping.
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Critically evaluate the operation of the most common analytical techniques used in the acquisition of genomic sequence and expression data
  • Apply various techniques to overcome the challenges of dealing with sequence data and be able to identify and apply appropriate software tools to tackle these challenges
  • Apply appropriate genome assembly software and optimise their outputs
  •  Perform gene expression profiling using both first and next generation sequencing data.
  • Demonstrate critical awareness of current practices and evaluate the relative strengths and weaknesses of the techniques covered and how these relate to the quality of the biological findings that result
  • Critically contrast a range of NGS tools and related sequence software tools for NGS applications, and interpret the output from those tools.

Proteome Informatics

Module Leader
Aim

    To provide an awareness of the current trends in proteomics and the crucial role that bioinformatics plays within this field.

    Module Leader: Prof Conrad Bessant

    Teaching team includes: Dr Lee Larcombe

Syllabus
    Introduction to practical proteomics (qualitative & quantitative), proteomics repositories (PRIDE, PeptidAtlas, etc.), structural biology, Protein/peptide identification algorithms (Mascot, X!Tandem, OMSSA), tools for quantitative proteomic data (from iTRAQ, SILAC, SRM, etc.).
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Explain the mode of operation of the most common analytical techniques used in the acquisition of proteomic data
  • Demonstrate critical awareness of current practices and recognise the relative strengths and weaknesses of the techniques covered and how these relate to the quality of the data acquired
  • Discover information using bioinformatics tools and effectively apply the information to biological problems.

Informatics for Metabolomics

Module Leader
  • Dr Fady Mohareb
Aim

    To explore the analytical and statistical techniques that are central to the field of metabolomics, and to introduce the emerging technologies that will generate yet more data in the future.

    Teaching Team includes: Dr Michael Cauchi and Dr Maria Anastasiadi.

Syllabus
    Introduction to metabolomics, NMR, LC-MS and GC-MS, advanced topics in R, multivariate classification (PLS-DA, SVMs, ANNs), Multiway analysis (PARAFAC), compound identification (e.g. spectral library searching), phenomics and biomarker discovery.
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Define common analytical techniques used in the acquisition of metabolomic data
  • Develop mathematical procedures covered during the module, to derive biological relevant information from metabolomics data sets
  • Develop critical awareness of various classification and regression models based on various analytical platforms

Programming Using Java

Module Leader
  • Dr Fady Mohareb
Aim

    To introduce the concepts of object-oriented programming using Java, the preeminent programming language for serious application development on the Internet. The module covers the basic fundamentals of programming in Java, with hands-on practical sessions on implementing programs using calculations, variables, control statements and loops.

    Teaching team includes: Corentin Molitor and Tomasz kurowski.


Syllabus
    Fundamental principles of programming, object-oriented programming using Java, variables and calculations, strings, arrays, GUI programming.
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Identify the most important programming structures.
  • Develop Java programs to meet given specifications.
  • Implement custom Java classes, interfaces, and packages.
  • Implement standalone application interfaces using Java Swing Components.

Data integration and Interaction Networks

Module Leader
Aim

    To introduce systems biology, systems methodologies, the most important bioinformatics software tools, and explain the algorithms that underpin them.

    Teaching team includes: Dr Fady Mohareb and Dr Enrico Ferrero.

Syllabus
    Introduction to Systems Biology, data standard protocols, database design and normalisation, designing Web-based interfaces using Java EE, introduction to interaction networks, data integration, data visualisation using Cytoscape.
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Utilise systems software for the visualisation of systems and system interactions
  • Critically apply available tools for data integration
  • Design, normalise and implement databases for experimental datasets
  • Develop critical awareness of the main data standards protocols for systems biology
  • Discover systems relationships between data using bioinformatics tools and approaches

Advanced Sequencing Informatics and Systems Biology

Module Leader
  • Dr Fady Mohareb
Aim

    To develop a system-level view of biological systems and their response to various internal and external factors, through the integration of advanced NGS sequencing data with functional annotation using concepts of mathematical simulation of biological systems.

    Teaching team includes: Dr Luca Bianco, Corentin Molitor, Dr Fady Mohareb and Dr Enrico Ferrero.

Syllabus
    de-novo sequence assembly, graph theory, networks dynamics, modelling systems, advanced Java programming.
Intended learning outcomes

On successful completion of this module a student should be able to:

  • Apply and optimise various algorithms for short and long reads sequence assembly
  • Integrate genomic and transcriptomic profiling with metabolic pathways
  • Utilise systems modelling software for the simulation of biological processes and system interactions
  • Extend the functionality of existing network visualisation tools through the development of various plugins Effectively apply graph theory and its application in biological data analysis.

Fees and funding

European Union students applying for university places in the 2017 to 2018 academic year and the 2018 to 2019 academic year will still have access to student funding support. Please see the UK Government’s announcement (21 April 2017).

Cranfield University welcomes applications from students from all over the world for our postgraduate programmes. The Home/EU student fees listed continue to apply to EU students.

MSc Full-time £8,500
MSc Part-time £1,635 *
  • * The annual registration fee is quoted above and will be invoiced annually. An additional fee of £1,340 per module is also payable on receipt of invoice. 
  • ** Fees can be paid in full up front, or in equal annual instalments, up to a maximum of two payments per year; first payment on or before registration and the second payment six months after the course start date. Students who complete their course before the initial end date will be invoiced the outstanding fee balance and must pay in full prior to graduation.

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2018 and 31 July 2019.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • A deposit may be payable, depending on your course.
  • Additional fees for extensions to the agreed registration period may be charged and can be found below.
  • Fee eligibility at the Home/EU rate is determined with reference to UK Government regulations. As a guiding principle, EU nationals (including UK) who are ordinarily resident in the EU pay Home/EU tuition fees, all other students (including those from the Channel Islands and Isle of Man) pay Overseas fees.

For further information regarding tuition fees, please refer to our fee notes.

MSc Full-time £19,000
MSc Part-time £19,000 **
  • * The annual registration fee is quoted above and will be invoiced annually. An additional fee of £1,340 per module is also payable on receipt of invoice. 
  • ** Fees can be paid in full up front, or in equal annual instalments, up to a maximum of two payments per year; first payment on or before registration and the second payment six months after the course start date. Students who complete their course before the initial end date will be invoiced the outstanding fee balance and must pay in full prior to graduation.

Fee notes:

  • The fees outlined apply to all students whose initial date of registration falls on or between 1 August 2018 and 31 July 2019.
  • All students pay the tuition fee set by the University for the full duration of their registration period agreed at their initial registration.
  • A deposit may be payable, depending on your course.
  • Additional fees for extensions to the agreed registration period may be charged and can be found below.
  • Fee eligibility at the Home/EU rate is determined with reference to UK Government regulations. As a guiding principle, EU nationals (including UK) who are ordinarily resident in the EU pay Home/EU tuition fees, all other students (including those from the Channel Islands and Isle of Man) pay Overseas fees.

For further information regarding tuition fees, please refer to our fee notes.

Funding Opportunities

To help students in finding and securing appropriate funding we have created a funding finder where you can search for suitable sources of funding by filtering the results to suit your needs. Visit the funding finder.

GREAT China Scholarship
The GREAT Cranfield University Scholarship China is jointly funded by Cranfield University and the British Council. Two scholarships of £11,000 each for Chinese students are available.

The Cranfield Scholarship

We have a limited number of scholarships available for candidates from around the world applying for the 2017 intake. Scholarships are awarded to applicants who show both aptitude and ability for the subject they are applying. Find out more about the Cranfield Scholarship

Postgraduate Loan from Student Finance England

A Postgraduate Loan is now available for UK and EU applicants to help you pay for your Master’s course. You can apply for a loan at GOV.UK

Santander MSc Scholarship

The Santander Scholarship at Cranfield University is worth £5,000 towards tuition fees for full-time master's courses. Check the scholarship page to find out if you are from an eligible Santander Universities programme country.

Chevening Scholarships

Chevening Scholarships are awarded to outstanding emerging leaders to pursue a one-year master’s at Cranfield university. The scholarship includes tuition fees, travel and monthly stipend for Master’s study.

Commonwealth Scholarships for Developing Countries

Students from developing countries who would not otherwise be able to study in the UK can apply for a Commonwealth Scholarship which includes tuition fees, travel and monthly stipend for Master’s study.

Future Finance Student Loans 

Future Finance offer student loans of up to £40,000 that can cover living costs and tuition fees for all student at Cranfield University.

Erasmus+ Student Loans

This new loan scheme for EU students is offered by Future Finance and European Investment Fund and provides smart, flexible loans of up to £9,300.

Cranfield Postgraduate Loan Scheme (CPLS)

The Cranfield Postgraduate Loan Scheme (CPLS) is a funding programme providing affordable tuition fee and maintenance loans for full-time UK/EU students studying technology-based MSc courses. 

Conacyt (Consejo Nacional de Ciencia y Tecnologia)

Cranfield offers competitive scholarships for Mexican students in conjunction with Conacyt (Consejo Nacional de Ciencia y Tecnologia) in science, technology and engineering. 

Chevening Scholarship

Chevening Scholarships are awarded to outstanding emerging leaders to pursue a one-year master’s at any UK university. 

GREAT India Scholarship 

The GREAT Cranfield University Scholarship India 2017 is jointly funded by Cranfield University and the British Council. Five scholarships of £5,000 each for Indian students are available.

Entry requirements

A first or second class UK Honours degree (or equivalent) in a life science, computer-science subject or candidates with appropriate professional experience.

The course is suitable for new graduates from a computer-science, life science or technology background who are interested in a career within the field of bioinformatics. The course is also ideal for professionals already working in the industry who would like to train to further their careers. The course is available on a full and part-time basis offering flexibility and support for those who wish to train whilst remaining in employment.

English Language

If you are an international student you will need to provide evidence that you have achieved a satisfactory test result in an English qualification. Our minimum requirements are as follows:

In addition to these minimum scores you are also expected to achieve a balanced score across all elements of the test. We reserve the right to reject any test score if any one element of the test score is too low.

We can only accept tests taken within two years of your registration date (with the exception of Cambridge English tests which have no expiry date).

Students requiring a Tier 4 (General) visa must ensure they can meet the English language requirements set out by UK Visas and Immigration (UKVI) and we recommend booking a IELTS for UKVI test.

Applicants who do not already meet the English language entry requirement for their chosen Cranfield course can apply to attend one of our Presessional English for Academic Purposes (EAP) courses. We offer Winter/Spring and Summer programmes each year to offer holders.

Your career

Bioinformatics is a fast-growing field that offers progressive career opportunities for forward-thinking people who are ready to grasp the challenge; people who understand both the biological and computing aspects of this science. 

Our MSc opens doors to careers in industry, public research establishments and university research. The multidisciplinary nature of our course has allowed our students to follow diverse career paths in various medical-related sectors including:

  • Pharmaceutical and Biotech companies
  • Plant research institutes
  • Food sector
  • Public Institutions
  • Bioinformatics
  • IT companies.

Previous students have gone on to jobs within prestigious institutions including:

Others have chosen to continue their research training by undertaking a PhD either at Cranfield or elsewhere.

Cranfield graduates are very successful in achieving relevant work. Some 93% are in relevant employment or further study six months after graduation. For professionals already in industry, Cranfield qualifications enhance their careers, benefiting both the candidate and their employer.

Cranfield Careers Service

Our Careers Service can help you find the job you want after leaving Cranfield. We will work with you to identify suitable opportunities and support you in the job application process for up to three years after graduation.

Cranfield Alumni

Thousands of graduates continue the ‘Cranfield experience’ after they leave by keeping in touch with colleagues and friends through free membership of Cranfield Alumni.

Students on campus

Living in Cranfield allowed me to connect with people from all over the world and broadened my horizons with social, cultural, and educational programs...this masters degree provided me with the knowledge to change into the field of Bioinformatics, where I always wanted to be.

Julia Feichtinger, PhD Student at the North West Cancer Research Fund Institute, Bangor University

Applying

Online application form. UK students are normally expected to attend an interview and financial support is best discussed at this time. Overseas and EU students may be interviewed by telephone.

Apply Now