Developing methods for the analysis of chromosome conformation data

Chromosome conformational data allows us to investigate the three dimensional structure of the genome. This project will involve developing novel computational and statistical methods for the analysis of genomic contact data. An initial focus will be on developing bioinformatics tools for the detection of Topologically Associating Domains (TADs) from Hi-C data and potentially developing software for use by the larger community. TADs are regions of the genome with higher than typical self-interactions and form boundaries between groups of genes within the genome. There is scope to apply a range of different methodologies in this context, so the project could apply machine learning approaches or Bayesian statistics, depending on the interests and experience of the student.