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Computational network deconstruction and synthetic pathway construction

This research seeks to build computational tools for designing or redesigning metabolic systems at various scales, ranging from a single pathway to whole cell to tissue. Our approach is to learn and adopt the design principles underlying the organization of both naturally occurring and man-made networks. Central to this approach is the notion that metabolic function is executed and controlled by complex interactions involving a network of substrates, enzymes, genes and other regulatory molecules. Current projects investigate the identification of functional units for biochemical transformation, i.e. pathways, and the interface between these units and the broader cellular network. In collaboration with Prof. Hassoun in Computer Science, we are developing computationally efficient algorithms to:

  1. select or construct a pathway of interest with specified features from annotated genome databases;
  2. deconstruct a network into minimally interdependent modules; and
  3. estimate, at varying resolutions, the functional behavior of metabolic modules from activity data.

These algorithms are developed and tested against both synthesis and analysis applications. As synthesis applications, we target heterologous production of naturally occurring biomolecules in Escherichia coli and chimeric cellulose in Acetobacter xylinum. As an analysis application, we study the biotransformation and elimination of drug compounds in the liver.