From 2010 until 2014, I was a postdoctoral scientist at the Biozentrum of the Universität Basel in Switzerland in the group of Erik van Nimwegen.
One of the major research topics of the group is that of gene regulation: how genes are switched on and off. (Nearly) every cell in a given person has (nearly) the same genetic code, but different cell types use that information to do amazingly different things. For example, heart muscle cells have radically different shape, makeup and functions from neurons in the brain, and can change their functions in response to changing external stimuli - even though the set of available genes is the same! So how do cells pick which genes to use at a given time?
The answer is complicated and not yet fully understood
During my postdoctoral research, I looked into how proteins called transcription factors dynamically regulate the expression of genes, and wrote code to take expression data from timecourse experiments and infer from that the regulatory network at the transcription factor level. I also looked at hCAGE data from the FANTOM5 project to explore the role of transcription factors during the earliest phases of embryogenesis.
Processing the large amounts of data which come from sequencing experiments requires quite a lot of computing power. Most of my code was written in R, MATLAB and Python, and executed on the BC2 High Performance Cluster.