Presenter

Dan's career as a computational systems biologist has included leadership roles in academic, corporate and national lab settings. His lab focuses on the development and subsequent application of mathematical, statistical and computational methods to biological datasets in order to yield new insights into complex biological systems. His lab's approaches include the use of Network Theory, Wavelet Theory, data analytics, and explainable-AI in a supercomputing context. These mathematical and statistical methods are applied to various population and (meta)multiomics data sets in an attempt to better understand the functional relationships as well as biosynthesis, signaling, transcriptional, translational, degradation and kinetic regulatory networks at play in biological organisms and communities. His group at ORNL studies many systems - from viruses to microbes to plants to humans. His lab is actively involved in the development of new exascale applications for biology.