Internal Research Groups
Biomedical Systems Analysis (BSA)
Computational and systems-biology based approaches to analysis and modelling of complex genetic systems in development and disease.
PROFESSOR RICHARD BALDOCK
Head of Biomedical Systems Analysis
Our Work
Biology and medicine are in the midst of a revolution, with high-throughput technologies (such as sequencing and imaging) transforming these disciplines into data-rich fields akin to particle physics. The sheer volume and complexity of these new data in turn demand revolutionary new mathematical, statistical and computational techniques for their analysis. There is no doubt that computational biology will be at the forefront of the new biology and medicine of the 21st century.
The BSA section is well positioned to handle the ongoing avalanche of new data, to understand the underlying complex systems, and to generate novel insights into human development, disease and evolution. Research in the BSA section ranges from large scale studies of genome evolution, genetic regulation of development, modeling and capturing embryo expression to complex disease and population studies.
Current Research
- Bioinformatics We are a computational biology group carrying out large-scale analyses of high-thoughput genomic, transcriptomic and proteomic datasets to test hypotheses in human evolution and disease. Our work has generated new insights into the evolution of regulatory systems encoded in the human genome and into disease processes such as cancer.
- Quantitative Genetics developing and applying tools for the analysis of complex traits across a range of species with a particular focus on human populations.
- The Mouse Atlas which pioneered the use of atlases for biomedical data and has developed a unique capability for 3D reconstruction and spatio-temporal data mapping onto standard spatial frameworks. Current research encompasses developmental anatomy ontologies, spatial pattern analysis and modelling of gene-expression data as well as intra- and inter-species interoperability through space and time.
- The EMAGE gene-expression database group manages the first spatially mapped gene-expression database developed as a resource for biomedical and systems biology research. The Editorial Group have pioneered techniques for gene-expression data curation and contributed to international standards.
- Modeling Regulatory Networks to understand mechanisms of development and disease and how evolution has molded them. We combine computational modeling and animal experimentation to characterise vertebrate regulatory networks. The computational research identifies associations between genes and DNA regulatory regions (e.g. using hidden Markov models and probabilistic networks) which are then investigated experimentally using zebrafish.
- Semantic Biomedical Knowledge Integration We develop semantics-based solutions for the integration of biomedical data and knowledge resources, focusing on the interoperability of digital biomedical atlases for systems biology and translational science.