BioHealth Informatics is a rapidly developing multi-disciplinary field that combines biological and genetic information with clinical data and computer information systems. It has been driven by the realisation that bio-informatics and health informatics must achieve a merger of standards, computer systems and data representations if progress is to continue towards the vision of post-genomic medicine.

To be updated shortly.

This module is delivered entirely via the internet, so a reliable internet commection is essential.
You will need access to a PC running a recent version of Microsoft Windows, preferably Windows XP or Windows 2000. You will also need Java version 1.2.2 or higher.

Anyone planning to use Bioconductor for the practical exercises may like to install and practise using R before the start of the course.

R can be downloaded from one of the mirrors listed on the R Project site. There is also a link from the R site to the Bioconductor project. You might also find an introductory R Tutorial useful.

On completion of this unit successful students will be able to:

1. Understand the opportunities arising from integrating bio- and health informatics datasets
2. Understand the barriers to interoperable bioinformatics and health informatics datasets
3. Handle and analyse bioinformatics and health informatics datasets
4. Cooperate and communicate ideas in a collaborative environment
5. Understand the process of project grant application and review

Using a number of high-profile biohealth informatics projects as examples the following areas will be identified and explored:

• Opportunities in the postgenomic world (phenotype and genotype). Examples include: Drug Discovery; Treatment Optimisation; Cross-species hypothesis generation Epidemiology and the UK Biobank
• Advanced Bioinformatics ? SNPs, transcriptomics, proteomics, metabolomics, epigenetics
• Data acquisition - Metadata & Provenance, Data Quality (myGrid)
• Data storage and access - web services, security, Grid computing, the Semantic Web
• in silico experimental workflows - documentation, repeatability and workflow management
• Applications - usability, visualization, dissemination, communication of results
• Sociology of Collaboration ? cultural differences of biology, computer science and medicine (evidence, safety, ownership, governance, regulation)
• Hazards ? ethics of genetic pedigrees; information overload and information underclasses

1. 2 written assignments and 1 oral presentation are required to complete this module: a short report presented in the format of a case for support of a grant application (LO5) (30%)
2. an extended report that details how to solve the integration of biohealth data (LO1, LO2, LO3, LO4) (50%), which will then presented as a short presentation in a seminar environment (LO4) (20%).

Exam: 50%, Coursework: 100%, Lab: 0%.

All the course materials are provided within the Moodle virtual learning environment (VLE). The tools provided will allow you to navigate and search through the course textbook, practical exercises and references to other useful texts and URLs. The course textbook is provided as a set of web pages. It will be used to provide the necessary background to the focus of the course, which is problem-based learning.

You will interact with the members of the course team, and with other learners, through course bulletin boards. Our students and graduates can use the programme bulletin boards after a course has ended, so we now have a large and supportive online community.