Biochemistry has classically involved the in-depth characterization of the molecular properties and functions of individual proteins. However, these proteins exist and function within complex matrices consisting of a vast array of biomolecules, ranging from small metabolites to large macromolecular structures. Thus, in vivo, the thousands of other unique molecules and their interactions will influence the function and evolution of each individual protein.
Systems-engineering principles are now being applied to elucidate how the cellular context influences each protein and how each protein influences cellular phenotype. This can be accomplished by treating each enzyme as a component in a vast network of proteins, and then modeling their interactions, as if the system were a chemical plant or electrical circuit. My work has involved the development of novel algorithms to integrate genome-scale data with these models to gain insight into how the network context influences evolution and how each protein contributes to phenotypes, such as disease.
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