Current postgraduate taught students
COMP60302: Introduction to BioHealth Informatics (2007-2008)
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.
The aim of this module is to introduce students to significant biohealth informatics themes and principles grounded by reference to high profile existing biohealth informatics projects and activities.
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
Assessment of Learning outcomes2 written assignments and 1 oral presentation are required to complete this module: (1) 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%).
Contribution to Programme Learning OutcomesContribution to programme learning outcomes: A1 (DA), A2 (DA), B2 (DA), B3 (DA), C1 (DA), C3 (DA), C4 (DA) and D2 (DA).
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