My goal in research is to better understand the tumor microenvironment by integrating multiple types of state-of-the-art high-resolution assays. My research interests involve the application of deep learning and transfer learning techniques to high throughput multi-modal molecular data. This can include DNA-seq, RNA-seq, ATAC-seq, proteomics, imaging, scRNA-seq, scATAC-seq, and Spatial Transcriptomics. I believe in a mix of service and research through my research faculty appointment. Therefore, I implement analysis pipelines for groups like the Multiple Myeloma team and also develop novel bioinformatics software packages. Specifically, I am working on two cancer projects right now.
The first project, which is funded by the Multiple Myeloma Research Foundation, is the study of subclones of myeloma cells found pre- and post-therapy from multiple myeloma patients. In this project, I am implementing an analysis pipeline for single cell multiomics to identify subclones associated with progression. We evaluate these cells with respect to gene expression and chromatin accessibility.
The second project, which is funded by the American Cancer Society Institutional Research Grant, is to study triple negative breast cancer at multiple levels of resolution. In this study which is set to begin this month, we will analyze single cell, imaging, and Spatial Transcriptomics from the same triple negative breast cancer sample. This research should lead to a better understanding of tumor and immune cell interactions resulting in new biomarkers and therapeutic targets.
Ph.D. - Ohio State University 05/2020