Our goal is to use experimental and statistical tools to construct a high dimensional picture of gene regulation, including cis and trans control of the full repertoire of RNAs expressed by cells. Currently, we are focusing on the function and biogenesis of circular RNA, which we recently discovered to be a ubiquitous and uncharacterized component of eukaryotic gene expression. A second major goal is to study gene expression variation in human cancer. Here, we combine mining massive public datasets, and experimental study of primary tumors and cell lines with bioinformatic and statistical methods. We use the cancer genome as window into functional roles played by RNA, and are attempting to characterize potential biomarkers.
- Machine/Statistical Learning
- Computational Biology