Dr Tim Beck
Research Fellow
Bioinformatics
Contact Details
I work at both the Cardiovascular Research Centre at the Glenfield Hospital, and the Adrian Building on the University campus.
Cardiovascular Research Centre: Room 3.05 Bioinformatics Hub
Tel: +44 (0)116 204 4732
Adrian Building: Room 210
Tel: +44 (0)116 229 7524
Email: timbeck@leicester.ac.uk
Background
BSc (Leeds); MRes (Leeds); PhD (Sussex)
I have experience of bioinformatics software and biomedical ontology development, semantics aspects of databasing, enabling data discovery, and knowledge exploitation for human and model organism based translational research.
Research Interests
- A graph database visualisation of part of SNOMED CT
My main focus is the use of semantics to connect health-related research big data to enable them to be aligned and compared, and for increased participant/sample sizes to be discovered for analysis. To be able to compare quantitative and qualitative values across big data we need to know if the values have the same meaning between data sets and the semantic rigour required to do this is provided by the use of ontologies.
Of particular interest to my work is the biomedical domain of "phenotype". There are several overlapping ontologies that describe phenotypes which have been developed for different purposes, for example SNOMED CT is used by the NHS and the Human Phenotype Ontology (HPO) is used by many research databases. If data sets are coded to different ontologies (e.g. clinical vs. research), or no ontology at all, then they can be linked to a common ontology via a process of harmonisation.
I am the Operational Lead for the world’s largest open access Genome Wide Association Study database, GWAS Central, which is developed in collaboration with the Brookes Bioinformatics Research Group. The resource provides advanced tools to allow visualisation, comparison and discovery of relevant summary-level genetic association data sets from the perspective of genes, genome regions or phenotypes. In this context, "phenotype" is used to define an aggregated set of medically and semantically distinct concepts, namely traits, medical signs and symptoms, and diseases. Each study is evaluated for its range of phenotype content and the most appropriate Medical Subject Heading (MeSH) and HPO terms are applied.
