We combine statistical, computational and biological approaches to study systems-level RNA expression with a focus on regulation of RNA in human cells and dysregulation in cancer. We focus on the use of data intenstive sequencing methods and are looking for students and post-docs interested in any of these areas to join us! Please contact Julia if you are interested.
Three major areas of research:
1) Circular RNA: We recently reported that across diverse cell types, the dominant RNA isoforms transcribed from hundreds of human genes are actually circular. This surprising and exciting finding promises to reveal new insights into RNA biology, and we are actively pursuing a more extensive study of this phenomenon.
2) Structural Variation in Human Cancer: We recently reported the first recurrent gene fusion in Serous Ovarian Cancer and are following up this and other structural variants in human cancers.
3) Statistical Approaches for Next-Generation Sequencing Data: We have developed rigorous statistical models for biological discovery. We are pursuing this direction of work, including approaches for computationally efficient statistical testing in massive sequencing data sets.