MSc Computational Biology

Course Code DNT1CG15102
Duration 1 Year
Attendance Full Time
Award Degree of Master of Science

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Course Profile
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Overview

Why take this course?

Two people talking picture
A major drive behind the revolution in molecular biology in recent years has been the remarkable advances in biotechnology that have led to cheaper, more accessible and more
reliable methods to generate vast amounts of biological data. In response to the rapidly growing demand for researchers with the right mix of computational skills and biological knowledge necessary to collect and analyse such data, the University of East Anglia (UEA) is one of the first UK universities to provide a cutting-edge MSc programme in the field of Computational Biology.

Built on the previous MSc Bioinformatics, the MSc programme is offered by the School of Computing Sciences (CMP) and run in close collaboration with the UEA School of Biological Sciences (BIO), the John Innes Centre (JIC), the Institute of Food Research (IFR ), The Sainsbury Laboratory (TSL), and the recently established Genome Analysis Centre (TGAC), all of which are located in close vicinity to the UEA in the Norwich Research Park.

The course provides a high quality and challenging postgraduate degree programme and is delivered by research scientists at the cutting-edge of their field. It equips students with the required skills and state-of-the-art knowledge in computational biology and bioinformatics to build successful careers in academia or industry.

A unique aspect of the programme is that up to seven scholarships are available to undertake projects at the associated research institutes. Project work may be done with companies and could involve paid placement at a company for high-profile students.

Contact time

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.

Teaching and Assessment

The course has two streams: Transcriptome Analysis diagram

One stream is aimed at students with a computing/mathematics/engineering background.
The other stream is aimed at students with a background in the Biological Sciences.

The course, which is also offered as a part time version (2 or 4 years), offers a 12 months full-time equivalent programme which starts with taught courses, brought to you by staff members of CMP, the Computational Biology Laboratory and BIO. In the final three months, a research project is undertaken either at CMP or in one of the above research institutes. The project is written up in the form of a dissertation and counts for one third of the final mark.

Some recent dissertation titles:

Integration of next-generation short-read assemblies for bacterial genomes
Computing planar phylogenetic networks
Predicting RNA pseudoknots
Virus-host co-evolution
Microtubules constrained to the surface of a cell
Loop modelling server for proteins
Molecular paleontology of repetitive DNA in yeasts
Next generation sequencing for transcriptome profiling and association genetics in complex plant genomes

Career opportunities

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 Geneticsin 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.

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.

Of course, you could instead opt to study for a PhD in computational biology in the School of Computing Sciences, one of the research institutes in the Norwich Research Park (NRP) or at other universities/research centres.

Within the context of pursuing a PhD it should be noted that NRP research studentships are available each year. These are generally based on collaborative projects between researchers working at NRP and are awarded on a competitive basis.

All of the students who completed the course in 2009 are now employed at The Genome Analysis Centre. (See Business Weekly 3rd March 2010).

The MSc Computational Biology at UEA gave me the concrete idea about 'what Bioinformatics is all about' though I knew the bioinformatics techniques theoretically but while studying at UEA I came to know about the application part of those techniques in the field of research. The course modules and the quality of teaching played the major important role in getting me a place as a 'Scientific programmer' at The Genome Analysis Centre, Norwich.

Shabhonam Caim, former student

I would highly recommend the MSc Computational Biology course at UEA in partnership with the Norwich Research Park (NRP), due to which I got this wonderful opportunity of working in NRP as a Scientific Programmer.

Purnima Pachori, former student

Contact: cmp.admiss@uea.ac.uk

Course Organiser

Dr Katharina Huber

Disclaimer

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.

Year 1

Year 1

Compulsory Study (130 credits)

Students will select 130 credits from the following module(s).

Name	Code	Credits	Period
Dissertation Reserved for postgraduates in the School of Computing Sciences, this module provides the student with a piece of individual work, with substantial research and practical elements. The subject of the dissertation will be determined by agreement between the student and his or her supervisor. The work may be undertaken as part of a large collaborative or group project. more...	CMPSMP6X	60	Semester 2
Fundamentals of Computational and Structural Genomics The module starts with recalling biological aspects of genomic information, gene and genome evolution. This is followed by an introduction of fundamental concepts and algorithms underpinning high-throughput sequencing/sequence assembly, sequence alignment, and analysis of genetic variance. This also includes a discussion of the most popular tools used for these purposes. In addition, fundamentals of protein structure will be introduced and some of the methods for structural bioinformatics will be discussed. Wherever appropriate, examples will be worked through. more...	CMPSMB4Y	30	Year Period
Genome Informatics This module provides an introduction to genome informatics. Topics covered include an introduction to new sequencing technologies and methods for analysing the data produced by them, transcriptomics, proteomics, and functional and comparative genome analysis. To a large extent, it will be taught by practitioners in the area from the Norwich Research Park. It is very much a research led course, where students gain an insight into the real-world challenges involved in the analysis of genomes. more...	CMPSMB32	10	Semester 2
Research Techniques 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 Computing Sciences and Computational Biology. more...	CMPSMP2Y	20	Year Period
Techniques for Biological Database Exploitation This module concerns the nature of biological data and how it is stored and made publicly accessible. Major public databases and software libraries in the bioinformatics domain will be introduced. These will include DNA sequence and protein sequence databases, as well as genome and micro-array databases. The student will be introduced to UNIX and LINUX for bioinformatics as well as PERL and BIOPERL. The course is taught predominantly by practicing bioinformaticians at the John Innes Centre. more...	CMPSMB36	10	Semester 2

Option A Study (50 credits)

Students will select 50 credits from the following module(s).

Name	Code	Credits	Period
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. more...	BIO-M109	10	Semester 1
Applications Programming 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. more...	CMPSMA23	20	Semester 1
Data Mining 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. more...	CMPSMC24	20	Semester 2
Database Manipulation This module introduces most aspects of databases, database manipulation and database management systems. The module is based on the relational model. Practical experience of database manipulation is provided through the use of SQL and the Java JDBC interface on a relational database management system. Database design is introduced using Entity-Relationship modelling and normalisation. Some high level language programming knowledge is desirable. more...	CMPSMB11	20	Semester 1
Information Retrieval and Natural Language Processing 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. more...	CMPSMB29	20	Semester 1
Internet & 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. more...	CMPSMB13	20	Semester 1
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. more...	CMPSMC32	10	Semester 2

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