Computational analyses of mammalian gene regulation The newly established Regulatory Genomics group at the Babraham Institute is studying how non-coding DNA sequence integrates inputs from signalling pathways, intrinsic transcription factors and chromatin structure to regulate gene expression. We have previously shown that regulatory regions may have a more flexible sequence organisation  and tolerate more mutations  than previously thought. It is known however that regulatory mutations may also lead to serious abnormalities , meaning that the principles of the regulatory 'grammar' and compensatory mechanisms that may 'buffer' aberrations in cis-regulatory networks are still poorly understood. You will address these questions using comparative genomics and population genetics analyses based on state-of-the-art global datasets, including the gene expression (RNAseq), transcription factor binding (ChIPseq) and chromatin conformation (e4C, promoter-capture Hi-C) data generated as part of the Babraham's Systems Biology of Ageing Programme that is run by our department. Assuming some prior experience in computer programming and basic quantitative skills, this project will provide opportunities to acquire extensive expertise in global genomic analyses and master the general approaches of learning from 'big data' that are applicable across disciplines. As the focus will be on the biological question, a biological background is desirable, although a first degree in a biological subject is not essential. There may also be opportunities to experimentally test hypotheses arising from in silico analyses in the 'wet lab'.
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