Basic Laboratory Research Themes in Oncology
Data Analysis and Modelling
Many of our basic laboratory research projects involve simultaneous analysis of thousands of samples and visualisation of molecular interactions. The ability to handle such huge datasets and to perform molecular modelling requires the development of increasingly sophisticated computational tools.
Within the Department we have extensive expertise in the development of methods for data analysis and modelling. This includes:
- Methods for analysis of microarray data (background correction, normalisation, quality control and down-stream analysis) from a variety of different platforms (spotted, bead and oligo arrays). We use microarray analysis to investigate DNA methylation and alternative gene splicing, to make comparisons between normal cells versus cancer cells, and human versus other species (CGH arrays). Linked to this, we also develop quantitative methods for identification of regulatory pathways and protein interaction networks.
- Statistical methods for whole genome association studies and for delineating the genetic basis of variation in gene expression, both essential for epidemiological studies.
- Statistical approaches for image analysis.
- Tools for molecular modelling, crucial for providing insight into stem cell fates and cancer epidemiology.
Research projects within this thematic includes:
- Shankar Balasubramanian - Structure, Function and Recognition of Nucleic Acids
- Paul Edwards - Chromosome Changes in Breast and Oesophageal Cancer
- Tony Green - Haematopoietic Stem Cells and Leukaemia
- Duncan Jodrell - Pharmacology and Drug Development Group
- Florian Markowetz - Computational Biology: Cancer Genetics & Genomics and Stem Cell Biology
- Nitzan Rosenfeld - Molecular and Computational Diagnostics
- Simon Tavaré - Statistical Bioinformatics and Computational Biology