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    <title>ML-Space</title>
    <subTitle>hybrid spatial Gillespie and Brownian motion simulation at multiple levels, and a rule-based description language</subTitle>
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    <namePart>Bittig, Arne T.</namePart>
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    <namePart>Uhrmacher, Adelinde</namePart>
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    <namePart>Faeder, James R.</namePart>
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    <namePart>Koeppl, Heinz</namePart>
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  <abstract type="Summary">Computer simulations of biological cells as well-stirred systems are well established but neglect the spatial distribution of key actors. In this thesis, a simulation algorithm "ML-Space" for spatial models with dynamic hierarchies is presented. It combines stochastic spatial algorithms in discretized space with individual particles moving in continuous space that have spatial extensions and can contain other particles. For formal descriptions of the systems to be simulated spatially, ML-Space provides a rule-based specification language.&lt;eng&gt;</abstract>
  <abstract type="Summary">Computersimulationen mikrobiologischer Prozesse, bei denen eine homogene Verteilung der Akteure einer Zelle angenommen wird, sind gut etabliert. In dieser Arbeit wird ein räumlicher Simulationsalgorithmus "ML-Space" für Mehrebenenmodelle vorgestellt, der auch dynamische Hierarchien abdeckt. Er vereint stochastische räumliche Algorithmen in diskretisiertem Raum mit individuellen Partikeln mit kontinuierlichen Koordinaten, die andere Partikel enthalten können. Zur formalen Beschreibung der räumlich zu simulierenden Systeme bietet ML-Space eine regelbasierte Modellierungssprache.&lt;ger&gt;</abstract>
  <note type="statement of responsibility">vorgelegt von Arne T. Bittig aus Rostock</note>
  <note type="thesis">Dissertation Universität Rostock 2017</note>
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      <publisher>Rostock : Universität, 2016</publisher>
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      <form>ix, 154 Seiten</form>
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      <namePart>Bittig, Arne T., 1980 - </namePart>
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