Jack, John; Rodríguez-Patón, Alfonso; Ibarra, Oscar H.; Păun, Andrei Discrete nondeterministic modeling of the Fas pathway. (English) Zbl 1175.68177 Int. J. Found. Comput. Sci. 19, No. 5, Part 1, 1147-1162 (2008). Summary: Computer modeling of molecular signaling cascades can provide useful insight into the underlying complexities of biological systems. We present a refined approach for the discrete modeling of protein interactions within the environment of a single cell. The technique we offer utilizes the Membrane Systems paradigm which, due to its hierarchical structure, lends itself readily to mimic the behavior of cells. Since our approach is nondeterministic and discrete, it provides an interesting contrast to the standard deterministic ordinary differential equations techniques. We argue that our approach may outperform ordinary differential equations when modeling systems with relatively low numbers of molecules – a frequent occurrence in cellular signaling cascades.Refinements over our previous modeling efforts include the addition of nondeterminism for handling reaction competition over limited reactants, increased efficiency in the storing and sorting of reaction waiting times, and modifications of the model reactions. Results of our discrete simulation of the type I and type II Fas-mediated apoptotic signaling cascade are illustrated and compared with two approaches: one based on ordinary differential equations and another based on the well-known Gillespie algorithm. Cited in 1 Document MSC: 68Q10 Modes of computation (nondeterministic, parallel, interactive, probabilistic, etc.) 92C37 Cell biology 92C40 Biochemistry, molecular biology Keywords:simulation of pathways; membrane systems; ODE; discrete simulation; nondeterministic simulation PDFBibTeX XMLCite \textit{J. Jack} et al., Int. J. Found. Comput. Sci. 19, No. 5, Part 1, 1147--1162 (2008; Zbl 1175.68177) Full Text: DOI References: [1] DOI: 10.1038/sj.cdd.4400371 · doi:10.1038/sj.cdd.4400371 [2] DOI: 10.1038/nsmb785 · doi:10.1038/nsmb785 [3] DOI: 10.1016/S1097-2765(01)00320-3 · doi:10.1016/S1097-2765(01)00320-3 [4] DOI: 10.1084/jem.187.3.403 · doi:10.1084/jem.187.3.403 [5] DOI: 10.1038/nm0295-129 · doi:10.1038/nm0295-129 [6] DOI: 10.1021/jp993732q · doi:10.1021/jp993732q [7] DOI: 10.1038/nrmicro1580 · doi:10.1038/nrmicro1580 [8] DOI: 10.4049/jimmunol.175.2.985 · doi:10.4049/jimmunol.175.2.985 [9] DOI: 10.1006/jmbi.1999.3060 · doi:10.1006/jmbi.1999.3060 [10] DOI: 10.1038/bjc.1972.33 · doi:10.1038/bjc.1972.33 [11] DOI: 10.1073/pnas.0501352102 · doi:10.1073/pnas.0501352102 [12] DOI: 10.1016/0092-8674(93)90509-O · doi:10.1016/0092-8674(93)90509-O [13] DOI: 10.1093/emboj/17.6.1675 · doi:10.1093/emboj/17.6.1675 [14] DOI: 10.1101/gad.10.22.2859 · doi:10.1101/gad.10.22.2859 [15] DOI: 10.1038/sj.cdd.4400822 · doi:10.1038/sj.cdd.4400822 [16] DOI: 10.1049/ip-syb:20050025 · doi:10.1049/ip-syb:20050025 [17] DOI: 10.1159/000085404 · doi:10.1159/000085404 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.