Cranos Williams

My primary research interests are in Systems Biology. Particularly, I am interested in the development of engineering-based systems approaches that effectively integrate information from multiple levels of biological abstraction. These approaches are used to facilitate the development of comprehensive theoretical and experimental techniques for modeling, understanding, and controlling biological processes at the tissue, cellular, and biochemical levels. Specific interests in this field include: nonlinear systems analysis, system identification, uncertainty analysis, optimal experimental design, and biological signal and data processing.
 
In corroboration with Ducoste and Isik, my primary role on this project is to develop a statistics-based signaling graph that describes the exchange of information between regulatory and metabolic pathways. The resulting graph will (a) identify control links (feedback, feed-forward, and functional redundancy controls) between TFs, genes, enzymes, and monolignols/metabolites, (b) integrate perturbation results following statistical analysis with a signaling diagram, and (c) computationally test hypotheses and rules for pathway regulation. Edges will describe the flow of information within and across components in the regulatory and metabolic pathways according to pair-wise relationships extracted from the statistical analysis. A dynamic learning algorithm will be used to iteratively train the signaling graph based on new perturbation data, potentially identifying new feedback and fee-forward edges.  The feedback and feed-forward edges identified by the algorithm will indicate potential new regulatory mechanisms.