Eichler, AnnikaAnnikaEichlerLichtenberg, GerwaldGerwaldLichtenberg2022-06-022022-06-022016-07Advances in Intelligent Systems and Computing 676: 198-221 (2018-01-01)http://hdl.handle.net/11420/12779In gene dynamics modeling, parameters of Boolean networks are identified from continuous data under various assumptions expressed by logical constraints. These constraints may restrict the dynamics of the network to the subclass of canalyzing or nested canalyzing functions, which are known to be appropriate for genetic networks. This paper introduces high performance algorithms, which solve the parameter identification problem by so called Zhegalkin identification and exploit the restriction to canalyzing or nested canalyzing functions resulting in reduced calculation time. The constraints are formulated in terms of orthogonal ternary vector lists, which offer an efficient representation for Boolean functions. The canalyzing constraints can be intrinsically incorporated in an existing Branch-and-Cut algorithm, which lead to a natural restriction of the search space and thus of the calculation time. For nested canalyzing constraints this is not possible. Instead, an identification algorithm based on enumeration is proposed. The algorithms are applied to mRNA micro array data from mice under different contaminant conditions and good correspondence to a known apoptotic pathway can be shown.enBoolean functionsGene dynamicsNetworksParameter identificationSystems biologyTernary logicInformatikConference Paper10.1007/978-3-319-69832-8_12Other