Bioinformatics and Statistical Genetics
This module will take you through exciting topics with many research opportunities within Oxford centred around following research areas: Large number of genomes have given us an unprecedented knowledge of molecular evolution, the nature of selection and the relationship of organisms. This revolution is not over. Data sets are still growing and even existing data is filled with opportunities for analysis and hypothesis testing. The mere size of these data sets pose new challenges to both models and algorithms. International collaborations such as the 1000 genomes (now much more) project has allowed the investigation of demographics, signatures of selection and not least recombination. Recombination is currently being elucidated in terms of signals, average rates and hotspots. Fast sequencing techniques gives incomplete information of the two diploid genomes and efficient algorithms are needed to handle the missing information. If sequence data is complemented with information about phenotypes, one is presented with finding the causal variants and their positions (Mapping), which is of tremendous value in moving toward functional dissection of diseases. Mapping is only a two-type data problem, but is being further enhanced by a series of other data types such as expression levels, concentration of small molecules (metabolomics) and information on proteins (proteomics) that would be fall into the category of Big Data and Integrative Genomics. Traditionally Bioinformatics have had a focus on sequences, but structures are following suit. Structures are closer to biological function and much more complex to analyse. This has lead to the fields of Structural Genomics and Structural Bioinformatics. Each day will typically contain about 50% lecturing covering concepts, models and computational issues before moving on to the result and challenges from recent large scale projects. The remaining 50% will have exercises, practicals and hands-on analysis of data.