Dr. Sebastian Triesch

I am interested in understanding how plants mediate differential gene expression in a spatiotemporal and condition-specific manner. To address this question, I use data generated by the massively parallel reporter assay Plant STARR-seq, which enables high-throughput characterization of genomic regulatory elements. Specifically, I use these data to train machine learning models that predict the regulatory activity of previously untested DNA sequences. These models can also be used to identify putatively functional regulatory motifs and to design tailor-made regulatory elements via in silico evolution.