Description of Course Modules

Computational/statistical modules

• Biocomputing I. Programming is an essential skill for bioinformaticians. This module focuses on Perl, the most widely-used programming language for bioinformatics. The module addresses a range of topics, including: how to write short scripts for handling biological data; how to use Bioperl to handle DNA and protein sequence data; and good programming practice for extended projects.
• Biocomputing II. Building on the preceding module, this covers advanced Perl programming topics, including how to create Web and database applications. Object-oriented programming in Java is taught using program design tools -- a UML (Unified Modeling Language) editor and the application development environment Eclipse.
• Data Management. With the rapid growth in the quantity of biological data, there is a growing need for bioinformaticians to manage data in an efficient and reliable manner. The first half of this module explains how to design, create and query relational databases using the Open Source software MySQL. In the second half of the module we cover other important data-handling topics: The use of XML for data exchange and for handling poorly-structured data (using the Open Source native XML database management system eXist); techniques for handling large data sets, including data warehousing and data mining; and the emergi ng scientific workflow paradigm for building database (and other) applications.
• Statistics. Provides a rigorous introduction to the essential statistics that underpin modern bioinformatics. Practical sessions focus on programming in R, which is rapidly becoming the most important (free) statistical analysis tool for bioinformatics applications.

Biological modules

• Sequence Analysis and Genomics. This module covers classical methods of biological sequence analysis and their applications to the problems of modern biology. It also discusses different aspects of molecular evolution: from sequence to structure and function.
• Molecular Structure. The School of Crystallography is famed for its research in the field of structural biology. In this module lecturers from the School teach the fundamentals of DNA and protein structure.
• Structural Bioinformatics. Proteins are the nanoscale machines that carry out the overwhelming majority of the essential processes in living organisms. Understanding how these machines work is an important area of current computational research that finds practical application in structure-based drug design. This module provides an introduction to the quantitative analysis and prediction of protein structure with a particular focus on the analysis of interactions with small molecules.
• Systems Biology. Systems biology is an emerging and challenging field that involves integrating information at different levels (e.g. molecules, cells, organs) in ways that aid our understanding of how a given biological system functions. In this module we focus on: some key sources of information that underpin systems biology research (microarray and proteomics data); the generic mathematical techniques and simulation software relevant to systems modelling; and various biological systems that are the focus of current systems biology research.