Titlebook: Computational Methods in Systems Biology; 11th International C Ashutosh Gupta,Thomas A. Henzinger Conference proceedings 2013 Springer-Verl

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Geir Ringen,Kjersti Øverbø Schultenguage. We extend the expressivity of an existing probabilistic programming language, Infer.NET Fun, in order to enable inference and simulation of CTMCs. We demonstrate our method on simple test cases, including a more complex model of gene expression. Our results suggest that this is a promising a

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Retrofit Concept for Textile Productionpiled and simulated in this framework, through the specification of a high-level interface for composing heterogeneous models. This is illustrated by a hybrid stochastic-differential model of bacteriophage T7 infection, and by a reconstruction of the hybrid model of the mammalian cell cycle regulati

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Alessandro Bertoni,Raj Jiten Machchharical reactions inside the cells. On a higher level, the molecular noise and other stochastic effects can lead to fundamentally different behavior of the cells in a population. As a consequence, average dynamics of a cell population are often not adequate to understand or control the dynamics of the

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Irene Roda,Marco Macchi,Luca FumagalliML-Rules, that allow a compact and concise description of these models. However, the more complex models become the more important is an efficient execution of these models. .-leaping algorithms can speed up the execution of biochemical reaction models significantly by introducing acceptable inaccur

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Hyun Woo Jeon,Vittaldas V. Prabhu adaptive uniformisation method introduced by Mateescu approximates the probability by neglecting insignificant states, and has proven to be effective for quantitative analysis of stochastic models arising in chemical and biological applications. However, this method has only been formulated for the

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Vittal Prabhu,Marco Taisch,Dimitris Kiritsissometimes to an inhibitive extent. By building bridges in existing models, we can exploit the advantages of each, widening the range of analysis possible for larger, more detailed models of gene regulatory networks. In this paper, we create just such a link between Process Hitting [6,7,8], a recentl

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