Abstract
To disentangle the numerical contribution of modules to the system-level behavior of a given biomodel, one often considers knock-out mutant models, investigating the change in the model behavior when modules are systematically included and excluded from the model architecture in all possible ways. We propose in this paper a Boolean approach for extracting conclusions about the role of each module from the systematic comparison of the numerical behavior of all knock-out mutants. We associate a Boolean variable to each module, expressing when the module is included in the architecture and when it is not. We can then express the satisfiability of system-level properties of the full model, such as efficiency, or economical use of resources, in terms of a Boolean formula expressing in a compact way which model architectures, i.e., which combinations of modules, give rise to the desired property. We demonstrate this method on a recently proposed computational model for the heat shock response in eukaryotes. We describe the contribution of each of its three feedback loops towards achieving an economical and effective heat shock response.