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Vascular Contraction Model Based on Multi-agent Systems

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11th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 616))

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Abstract

This paper presents a first approximation to the simulation of vascular smooth muscle cell following an agent-based simulation approach. This simulation incorporates mathematical models that describe the behaviour of these cells, which are used by the agents in order to emulate vascular contraction. A first tool, implemented in Netlogo, is provided to allow the performance of the proposed simulation.

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Notes

  1. 1.

    https://ccl.northwestern.edu/netlogo/.

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Author information

Authors and Affiliations

  1. D. Sistemas Informáticos y Computación, Universitat Politècnica de València, València, Spain

    J. A. Rincon, V. Julian & C. Carrascosa

  2. Departamento de Fisiologìa, Universitat de València, València, Spain

    Guerra-Ojeda Sol

Authors
  1. J. A. Rincon
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  2. Guerra-Ojeda Sol
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  3. V. Julian
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  4. C. Carrascosa
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Corresponding authors

Correspondence to J. A. Rincon , Guerra-Ojeda Sol , V. Julian or C. Carrascosa .

Editor information

Editors and Affiliations

  1. Escuela Superior de Ingeniería Informática, Universidad de Vigo , Ourense, Spain

    Florentino Fdez-Riverola

  2. Faculty of Computing, Universiti Teknologi Malaysia , Johor, Johor, Malaysia

    Mohd Saberi Mohamad

  3. Department de Informática, Universidade do Minho , Braga, Portugal

    Miguel Rocha

  4. Departamento de Informática y Automática, Universidad de Salamanca , Salamanca, Spain

    Juan F. De Paz

  5. Departamento de Informática y Automática, Universidad de Salamanca , Salamanca, Spain

    Tiago Pinto

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Rincon, J.A., Sol, GO., Julian, V., Carrascosa, C. (2017). Vascular Contraction Model Based on Multi-agent Systems. In: Fdez-Riverola, F., Mohamad, M., Rocha, M., De Paz, J., Pinto, T. (eds) 11th International Conference on Practical Applications of Computational Biology & Bioinformatics. PACBB 2017. Advances in Intelligent Systems and Computing, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-60816-7_25

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  • DOI: https://doi.org/10.1007/978-3-319-60816-7_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60815-0

  • Online ISBN: 978-3-319-60816-7

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