Applications and challenges in mathematical modeling of metabolic networks

Daniel Segre
Boston University

Cellular metabolism consists of a complex network of chemical reactions, which provide the cell with a reliable supply of energy and building blocks. Learning how this network responds to environmental and genetic perturbations is a fundamental open question, relevant for understanding physiological and evolutionary adaptation, for fighting metabolic and infectious diseases, and for metabolic engineering of industrially important microbes. Optimization approaches based on steady state approximations of metabolic networks have become one of the main frameworks for addressing these questions, and one of the flagship methods in systems biology. I will discuss some ongoing applications and challenges in this field, including the study of nonlinearities ("epistasis") in how multiple genetic perturbations combine with each other, and the extension from individual microbes to artificial and naturally occurring microbial ecosystems.

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