Assistant Professor, Public Health Sciences
- BS, Physics, Wright State University
- PhD, Physics, University of Maryland
- Postdoctoral Fellowship, Computational Biology, Harvard University
Bioinformatics and Genomics, Biomedical Engineering, Computational Biology, Genetics, Molecular Physiology and Biological Physics
gene regulatory networks, systems genetics, multi-omic data integration, network science
My research program lies at the intersection of network science, genomics, and systems genetics to develop computational methods that model the collective regulatory effects that modulate human phenotypes, including disease. Network methods provide flexible, quantitative representations of complex associations that occur between interacting biomolecules. In addition, they are generally computationally efficient, scale well to large data sets, and can link together diverse biological elements based on mechanistic information. Despite successes in applying network methods to genomics, many open questions remain regarding their use in systems genetics and post- transcriptional gene regulation. Currently, I am particularly interested in two questions: (1) How does non-coding genetic variation alter transcription factor (TF) regulatory networks? (2) What are the best ways to model post-transcriptional regulatory networks in human disease phenotypes?