John’s research involves creating and applying computational methods to study epigenetics, especially DNA methylation. He developed the MIRA R package for inferring regulatory information from DNA methylation and the PCRSA R package for using PCA to understanding major sources of variation in DNA methylation data. On the application side, he studies the epigenetics of acute myeloid leukemia.
Derek is currently developing mechanics-based computational models of skeletal and cardiac muscle growth and remodeling. He uses big data to aid in the identification of best predictors of both cardiac left ventricular and skeletal muscle growth in large clinical datasets and compilations of experimental data. Additionally, he plans to use a big data approach to decrease computation time and increase the feasibility of constructing patient-specific models.
Cassie is a PhD student in the Center for Public Health Genomics and the Department of Biochemistry and Molecular Genetics. Broadly, she is interested in what causes a disease to develop in some, but not most, individuals. Currently, she studies genetic determinants of type 1 diabetes. By comparing global genetic variation in individuals with diabetes to those without, she aims to identify novel genetic risk factors and refine our understanding of the “genetic architecture” of this disease. She plans to integrate analysis of immunological phenotypes, genetic variation, gene expression, and chromatin state to better understand what goes wrong during disease development and progression. Using this systems genetics approach, she hopes to identify biological pathways driving disease and develop improved tools for screening, early detection, and (one day) prevention of type 1 diabetes.
Sarah studies the signaling and gene regulatory networks underlying changes in synaptic connectivity throughout development and across disease states by integrating various -omics datasets and mass cytometry with synaptic and lineage tracing approaches.
Cailey is working to develop an optimal transport-based end-to-end classification system for biomedical image data. Her research is based on mathematical theory applications to image and signal processing problems. One of her goals is to leverage the information rendered by transport-based image transformations to provide biologically meaningful explanations for class differences in biomedical data.
Alex is investigating the ability of Focused Ultrasound, a non-invasive tissue ablation technology, to enhance the immune response to cancer. Specifically, he is interested in combining high-throughput experimental data with systems biology approaches to understand the mechanisms driving this immunogenicity. He hopes to leverage this knowledge to design synergistic Focused Ultrasound-Immunotherapy combination strategies capable of conferring primary and immunological tumor growth control.