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This Thesis presents research at the boundary between Statistical Physics andBiology. First, we have devised a class of Boolean constraint satisfactionproblems (CSP) whose solutions describe the feasible operational states of achemical reaction network. After developing statistical mechanics techniques togenerate solutions and studying the properties of the solution space for bothensembles and individual instances of random reaction networks, we have appliedthis framework to the metabolic network of the bacterium E.Coli. Resultshighlight, on one hand, a complex organization of operational states into"modules" involving different biochemically-defined pathways, and, on theother, a high degree of cross-talk between modules. In summary, we propose thatthis class of CSPs may provide novel and useful quantitative informationlinking structure to function in cellular reaction networks.

Boolean constraint satisfaction problems for reaction networks