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Accelerated Simulation of Hybrid Biological Models with Quasi-Disjoint Deterministic and Stochastic Subnets

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Hybrid Systems Biology (HSB 2016)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 9957))

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Abstract

Computational biological models are indispensable tools for in silico hypothesis testing. But with the increasing complexity of biological systems, traditional simulators become inefficient to tackle emerging computational challenges. Hybrid simulation, which combines deterministic and stochastic parts, is a promising direction to deal with such challenges. However, currently existing algorithms of hybrid simulation are impractical for implementing real and complex biological systems. One reason for such limitation is that the performance of hybrid simulation not only relies on the number of stochastic events, but also on the type as well as the efficiency of the deterministic solver. In this paper, a new method is proposed for improving the performance of hybrid simulators by reducing the frequent reinitialisation of the deterministic solver. The proposed approach works well with models that contain a substantial number of stochastic events and higher numbers of continuous variables with limited connections between the deterministic and stochastic regimes. We tested these improvements on a number of case studies and it turns out that, for certain examples, the amended algorithm is ten times faster than the exact method.

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Acknowledgments

This work has been partially funded by the GE-SEED grant (7934) which is administrated by STDF(Science and Technology Development Fund, Egypt) and DAAD (German Academic Exchange Service). We also acknowledge the helpful comments of the anonymous reviewers for improving a previous version of the paper.

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Authors and Affiliations

  1. Department of Mathematics and Computer Science, Faculty of Science, Port Said University, Port Said, 42521, Egypt

    Mostafa Herajy

  2. Computer Science Institute, Brandenburg University of Technology, Postbox 10 13 44, 03013, Cottbus, Germany

    Monika Heiner

Authors
  1. Mostafa Herajy
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  2. Monika Heiner
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Correspondence to Mostafa Herajy .

Editor information

Editors and Affiliations

  1. INRIA Grenoble - Rhone-Alpes , Saint-Ismier, France

    Eugenio Cinquemani

  2. Electrical Engineering/Computer Science, University of California at Berkeley , Berkeley, California, USA

    Alexandre Donzé

A Reactions of the Circadian Oscillation Model

A Reactions of the Circadian Oscillation Model

Table 3 provides a complete specification of the circadian oscillation model [32] used in Sect. 4.1, This reaction set has been derived from the system of ODEs given in [32] following the approach described in [13]. The given ODEs fulfil the criteria established in [29]; so the result is unique. See [3] for a graphical representation of this reaction set by use of Petri nets and their treatment in the different paradigms.

Table 3. The reaction set of the circadian oscillation model
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Herajy, M., Heiner, M. (2016). Accelerated Simulation of Hybrid Biological Models with Quasi-Disjoint Deterministic and Stochastic Subnets. In: Cinquemani, E., Donzé, A. (eds) Hybrid Systems Biology. HSB 2016. Lecture Notes in Computer Science(), vol 9957. Springer, Cham. https://doi.org/10.1007/978-3-319-47151-8_2

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  • DOI: https://doi.org/10.1007/978-3-319-47151-8_2

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