Duration

The MSc in Bioinformatics is a one year full-time course. The next starting date is 7 January 2013.

Entry Requirements

You have a first or second class Honours degree in Biological Sciences or a related scientific discipline, or an equivalent qualification. Alternatively, if you have several years of appropriate experience in industry you are also encouraged to apply. As overseas applicant you will be required to demonstrate your level of proficiency in English, e.g. a IELTS score of 6.5.

Course Aims

The course aims to respond to the need for Bioinformaticians by teaching Biological Sciences graduates the theoretical and practical analytical skills used in Bioinformatics. A four-month project placement in industry, in a research institute or in a University research laboratory is an integral part of the course. The course prepares you for employment in industry or academia either directly or as the result of subsequent study.

Computers

You work on a Linux laptop on which you install and develop your own Bioinformatics toolkit. During the course this laptop is provided as a loan by the University of Leicester. The ownership of the laptop will be transferred free of charge to you on the successful completion of the course. Also, all students have access to the course server during the course.

Fees

Find out about course fees.

Deposit

To ensure that a laptop is in place for you at the start of the course we ask you for a deposit of £750. This deposit will be offset against your course fees. We will guarantee a properly equipped laptop for every student from whom we have received the deposit by 15 November 2012.

Studentships

Information on scholarships available for international students.

Teaching and Assessment Methods

As Bioinformatics is a very practical subject you are taught using a combination of lectures, problem solving exercises, small group work, formally constructed practical sessions and self-directed learning. Each taught module is assessed by continuous assessment and by a written examination. The steered research project is assessed on project performance, demonstrated programming skills, an oral presentation and the quality of written work. The independent research project is assessed on the student’s independence, initiative and understanding whilst undertaking the project, a final oral presentation and the submission of a final dissertation. Additionally, at the end of the course all students are given the opportunity of a viva voce examination by the external examiner.

Course Modules

Core Modules: (January-May):

• Introduction to UNIX and Linux - essential computing skills This module provides tuition in the basic skills necessary to progress through the masters degree. We begin with an introduction to Ubuntu Linux and how to configure your computer to allow access to local file-storage systems, e-mail, FTP servers, and to useful sites on the internet. Next, we deal with the installation of software and applying updates & patches. The next component deals with the details of the Linux operating system including files, archives and compression systems. This provides a basis for more advanced aspects of configuring the computer and installing software. An introduction to Hypertext Markup Language (HTML) and Cascading Style Sheets (CSS) follows, providing a basic grounding in the concepts of web-page design.
  
• Programming: Java and Databases for Bioinformatics This module strengthens the basic ideas involved in developing a piece of software to solve a problem. It illustrates these ideas by presenting fundamental elements of the programming language Java. It also introduces Graphical User Interfaces and applets. Furthermore, this module teaches both, the use of computer databases, and how they can be designed and built. The focus is on principles common to computer databases across all disciplines, but exercises will focus on biological examples with the objective to use the theory to build and query biological relational databases.
• Programming: Perl for Bioinformatics Perl is a simple scripting language that allows managing bioinformatics housekeeping tasks, but is at the same time powerful enough to be used in the majority of bioinformatics webservers. We teach key commands and the most typical programming structures used in Perl. Following the material covered in the interactive lectures you solve small programming problems in the afternoon tutorials to improve your programming skills. The module aims to develop your programming so that you are able to write Perl programs in a Bioinformatics environment under the consideration of already existing solutions and structures in public domain databases such as CPAN and BioPerl.
• Algorithms for Bioinformatics Processing biological data requires complex computations on large volumes of data. To ensure that these computations complete within a reasonable amount of time, one must design appropriate algorithms (computer procedures) after a careful study of the characteristics of the underlying data and making use of existing algorithm design principles. This module introduces you to the algorithmic solution of computational problems in bioinformatics and also covers the probabilistic models that underlie the formulation of biological data processing tasks as computational problems.
• Gene and genome analysis This module aims to put into context the very broad role of bioinformatics in the fields of genetics and genomics. It includes introductory sessions on the basic molecular and cellular processes underlying gene expression, genome structure and evolution as well as the techniques used to study them. As a major application of bioinformatics, genome sequencing projects and genome annotation are covered in lectures, workshops and computer practical classes and the emerging areas of functional and comparative genomics are also explored. Since statistical analyses underpin many informatic challenges in biology, these analyses and the statistical tools supporting them (specifically the R programming language) are investigated in the context of two major application areas: transcriptomics (focussing on microarrays) and molecular evolution and phylogeny. In addition the role of statistics in genetic mapping and genetic epidemiology is taught.
  
• Proteins The aim of this module is to provide you with an understanding of the basic features of the three-dimensional structures of proteins and of the tools available to determine, visualise and analyse them. It includes brief introductions to the experimental methods, X-ray crystallography and NMR spectroscopy, used to determine protein structure and to the ways in which the quality of the structures obtained can be assessed. A central feature of the module is detailed training in the retrieval of protein structures from databases and the visualisation and comparison of these structures. The module also covers in detail the alignment and comparison of amino acid sequences and the use of such comparisons to derive models of protein structure. We also discuss the use of structural information on proteins in the drug design process, including visiting speakers from the pharmaceutical industry. Proteomics is covered in a day of lectures and practical exercises from guest speakers expert in this rapidly developing area.

Steered research project: (June - August):

The project incorporates training in the analysis of next generation sequencing data, statistical analysis, web-server development and programming. Generic training will be given during this period, including web page development, presentation skills and communication skills.

Independent research projects: (September - December):

Building on the skills acquired in the taught modules and the steered research project, each student undertakes a project involving original, independent research. The project is carried out under individual supervision in an approved company, external research institution or in the laboratory of a member of academic staff.