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Faculty of Science Postgraduate Brochure (PDF)
IELTS: 6.5 (minimum 6.0 in all components)
Faculty of Science Scholarships
Postgraduate Admissions Office
MSc Computational Biology
Degree of Master of Science
School of Study
Dr. Katharina Huber
Why take this course?
Much of the future of Biology lies in genomics. Genomes can now be sequenced in an hour generating a tsunami of data. This step change in our ability to generate and analyze genomic data has resulted in a rapidly growing demand in researchers with the right mix of computational skills and biological knowledge necessary to make the new discoveries of what is hidden in these genomes.The MSc in Computational Biology is a high quality and challenging postgraduate degree program aimed at equipping students with the required skills and state-of-the-art knowledge in computational biology and bioinformatics to build successful careers in academia or industry.
You will be trained in:
- Next Generation Sequencing (NGS) genetics,
- High throughput analysis pipelinex
- Genomics and Transcriptomocs.
Who will do the training:
You will receive training by world leaders working at the Norwich Research Park (NRP) including the University of East Anglia (UEA), The Genome Analysis Center (TGAC), The Institute of Food Research (IFR), and the Sainsbury Lab (TSL) with input also from the John Innes Center (JIC).
If you hold a degree in the life sciences, we will provide you with the computing skills (incl programming). Also you will learn about the basic principles underpinning some of the most popular approaches used in genomics.
If you hold a computing degree or related, you will leant about how computer science tools and techniques can be made to work to tackle exciting challenges surrounding big data.
The program is available as a 1 year full-time course, or as a 2 year or 4 year part-time course.
Teaching and Assessment
The assessment of the modules that the program is made up of is via a combination of coursework, exam, and oral presentation. MSc dissertation projects can be undertaken either at the School or at one of NRP's research institutes .
Students have on average 15 hours of contact time per week with teaching staff through lectures, laboratory sessions and seminars, though this may vary depending on module choices. Additionally, students should allocate at least 25 hours per week for study, coursework assignments and projects.
Many of the students graduating from the program have gone on to pursue a PhD at highly respected national and international research institutes and universities. Others have found jobs in industry working as, for example, scientific programmers.
Various research institutes in the UK offer jobs in computational biology and bioinformatics and systems biology, including the Wellcome Trust Sanger Institute Centre, the European Bioinformatics Institute, Wellcome Trust Centre for Human Genetics in Oxford and the various UK research centers for Systems Biology. Pharmaceutical companies such as GlaxoSmithKline or AstraZeneca also recruit regularly, but smaller companies also employ bioinformaticians including those involved in agricultural applications, biotechnology, environmental sciences and food research.
PhD Students interested in pursuing a PhD in computational biology can do so in the School working with experienced supervisors working at the forefront of their field, one of the research institutes within NRP, or at other universities/research centres. Within this context it should be noted that NRP research studentships are available each year. These are generally based on collaborative projects between researchers working within NRP and are awarded on a competitive basis.
Job Advertisements Magazines such as Nature, Science and New Scientist often feature relevant job advertisements, as well as Bioinformatics.org, Bioinformatics.fr, biohealthmatics.com and biocareers.org.
The MSc in Computational Biology offered by UEA is an in-depth, hands-on, overview of the application of computing and programming to a broad range of biological problems. The collaboration with the Norwich Research Park also allowed me to gain valuable insight into the current bioinformatic research environment. The course was thoroughly interesting and inspired me to start a PhD in Computational Biology.
I really enjoyed my course and the one year that I spent in UEA. The course really helped me realize the direction of my research interests. I found the course to be a good balance of computational and non computational modules. And even though it was an extremely busy one year, the excellent support from the tutors and other support staff made it less challenging.
I really did have a great time at UEA. I am happy to inform you that I have been accepted for a PHD position in Vienna, Austria which is jointly offered by the Austrian Centre of Industrial Biotechnology and the University of Natural Resources and Life Sciences (BOKU), Vienna and will be starting on 1 November, 2011. I will be working on the metabolic modelling and reconstruction of different E. coli strains. The MSc Computational Biology program has contributed greatly towards me getting this offer.
I have great memories of my year at University of East Anglia, thanks to the quality of the courses and the professors which helped getting me a place as 'Bioinformatician'at Biocon India. Studying at UEA have brought an added value to my personal life. I would also like to mention the practical knowledge and exposure that was given to me during my dissertation at Institute of Food Research have prepared me for working life in order to quickly become professional at end of my studies. I would highly recommend the MSc Computational Biology program at UEA.
Mohammed Obaid Siddiqui
Faculty of Science Postgraduate Brochure (PDF)
- 95% of research activity was classified as internationally leading, excellent or recognised in the 2008 Research Assessment Exercise.
- Our Masters programmes are accredited by the BCS - The Chartered Institute for IT to full Chartered IT Professional (CITP Further Learning Element) as well as leading to Chartered Engineer (CEng) status.
- The School maintains close links with industry and many of our student assignments relate to real world problems.
- The School of Computing Sciences leads the university in utilizing its internationally recognized research commercially, through SYS Consulting, its Consulting company and through Knowledge Transfer Partnerships.
- Our students also use their technical and entrepreneurial skills to play influential roles in the creation of companies such as Travel Republic, Evoke systems, Fyfo and Shoretech systems.
Come and Visit Us
Our Open Days will give you the opportunity to experience the University of East Anglia's unique campus atmosphere.
Compulsory Study (130 credits)
Students must study the following modules for 130 credits:
In this module, each Masters student is required to carry out project work with substantial research and practical elements on a specified topic for their MSc dissertation from January to late August. The topic can be chosen and allocated from the lists of proposals from faculty members, or proposed by students themselves with an agreement from their supervisor and also an approval from the module organiser. The work may be undertaken as part of a large collaborative or group project. A dissertation must be written as the outcome of the module
FUNDAMENTALS OF COMPUTATIONAL AND STRUCTURAL GENOMICS
The initial section of the module will revise biological aspects of genomic information, gene and genome evolution. Examples will be worked through for evaluating sequence data and to recognise problems of sequence data analyses. Gene annotation and gene searching procedures will be introduced and approaches for phylogenetic analyses will also be covered. Following that, sequence alignment and sequence recognition protocols will be investigated and algorithms for this purpose will be examined. Understanding of the experimental techniques used to determine protein structure will be explained and in particular emphasis is paid to the detection of errors in these structures. From there methods used to predict protein structures will be covered. These will include secondary structure prediction, fold recognition (threading) and homology modelling. Some of the methods introduced earlier, such as profiles, will reappear in the context of structure prediction so consolidating understanding of these concepts. In addition the methods of molecular mechanics will be presented together with a general introduction to protein dynamics.
This module is very much a research led course and is largely taught by scientists from across Norwich Research Park. It aims to introduce students to current trends, developments, and techniques in genomics based Computational Biology. It forms part of the MSc Computational Biology Programme, but may also be taken by MNatSci students on route U1CGF0401 who have previously taken CMPSMB4Y or CMPC3B06.
A module that provides students with the training of some transferable skills, an overview of research methods used in computing sciences, and introduces individual students to background material preparatory to their dissertation project which they would not otherwise study systematically to the required depth. The learning objectives for this module are to enable students to approach the dissertation with the intellectual and practical skills necessary to successfully complete a masters dissertation in Computer Science.
Option A Study (50 credits)
Students will select 50 credits from the following modules:
BIOLOGY Stream students MUST take CMPSMA23, CMPSMB11 and CMPSMC32. COMPUTING Stream students MUST take CMPSMC24 and BIO-M109, they must ALSO choose one module from CMPSMB13, CMPSMB29 or CMPSMA23.
This module aims to establish a clear understanding of the Object Oriented Programming paradigm, including Encapsulation, Inheritance and Polymorphism. Simple data structures will be considered and classes will be indentified as vehicles for implementing abstract data types. The benefits of modular software design will be emphasised and the Unified Modelling Language (UML) will be introduced as a design tool for large software systems. Topics include: Data structures, programming, and program design.
This module is designed for postgraduate students studying on MSc courses. The module explores the methodologies of Knowledge Discovery and Data Mining (KDD). It aims to cover each stage of the KDD process, including preliminary data exploration, data cleansing, pre-processing and the various data analysis tasks that fall under the heading of data mining. Through this module, students should gain knowledge of algorithms and methods for data analysis, as well as practical experience using leading KDD software packages.
This module provides an overview of the philosophy and development of database technology. Practical experience of database manipulation is provided through the use of SQL and the Java JDBC interface on the IBM DB2 database management system. Database design is introduced using Entity-Relationship modelling and normalisation.
GENETICS, GENOMICS AND BIOINFORMATICS
This module provides a Master's level introduction to the structure and function of DNA and its inheritance in pro- and eukaryotic organisms. It also includes an introduction to the study of the genomes of model organisms, together with the analysis of gene function and expression. An introduction to the role of bioinformatics in studies of evolution and genomics is also included. This module forms the foundation for more in-depth coverage of these topics later in the academic year.
Nowadays, millions of people worldwide make use of IR systems every day via search engines, and the exponential increase in the number of websites and documents available means that these systems have been developed to be highly efficient. In this module, we will cover the essential theoretical ideas that underpin modern information retrieval (e.g. the vector-space model, probabilistic approaches, relevance feedback etc.) and examine how they are practically implemented in current systems. Lecture material is re-enforced by a set of laboratory exercises and an assessment that enable you to implement some of these ideas practically. We also examine natural language processing techniques that are increasingly used in IR, and the emerging technologies of audio and video retrieval.
INTERNET and MULTIMEDIA TECHNIQUES
This module surveys the current and emerging technologies of the Internet and its impact on society, particularly e-commerce. The practical part of the module concentrates on the design and integration of web sites, using a range of tools and techniques in current use.
MATHEMATICS AND ALGORITHMS FOR COMPUTATIONAL BIOLOGY
This module introduces core concepts and approaches in graph theory, clustering, algorithm analysis and statistics. This will provide a sound mathematical foundation for Computational Biology techniques and research.
Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules and regular (five-yearly) review of course programmes. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, there will normally be prior consultation of students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff or sabbatical leave. Where this is the case, the University will endeavour to inform students.
- Degree Subject:
- Computing Sciences, Biological or Life Sciences, Mathematics and Engineering.
- Degree Classification:
- Good first degree (minimum 2.1 or equivalent).
Students for whom English is a Foreign language
We welcome applications from students whose first language is not English. To ensure such students benefit from postgraduate study, we require evidence of proficiency in English. Our usual entry requirements are as follows:
IELTS: 6.5 (minimum 6.0 in all components)
TOEFL: Internet-based score of 88 (minimum 18 in listening, 21 speaking, 19 writing and 20 reading)
PTE (Pearson): 62 (minimum 55 in all components)
Test dates should be within two years of the course start date.
Other tests such as TOEIC and the Cambridge Certificate of Advanced English are also accepted by the university. Please check with the Admissions Office for further details including the scores or grades required.
INTO UEA and INTO UEA London run pre-sessional courses which can be taken prior to the start of your course. For further information and to see if you qualify please contact email@example.com (INTO UEA Norwich) or firstname.lastname@example.org (INTO UEA London).
Fees and Funding
Tuition Fees 2013/14
- UK/EU £5,000
- International £12,500
- International applicants applying to this course can be considered for one Faculty of Science half fees scholarship or one £2000 scholarship. The deadline is 1st April 2013.
Faculty of Science Scholarships
Students wishing to apply should submit an essay answering the following question in 1000 words: 'Cohen said ' Mathematics is biology's next microscope only better; Biology is mathematic's next physics only better'. Many people would extend this to 'Computer Science is biology's next microscope only better; Biology is computer sciences next physics only better'. Discuss. Essays should be emailed to the Admissions Office. Please ensure you include your full name, the course you have applied to, and your applicant number in your email.
For more information please contact the Computing Sciences Postgraduate Admissions Office (email@example.com).
Applications for Postgraduate Taught programmes at the University of East Anglia should be made directly to the University.
To request further information & to be kept up to date with news & events please use our online enquiry form.
If you would like to discuss your individual circumstances prior to applying please do contact us:
Postgraduate Admissions Office
Tel: +44 (0)1603 591515
International candidates are also encouraged to access the International Students section of our website.