Explicit Calculation of Structural Commutation Relations for Stochastic and Dynamical Graph Grammar Rule Operators in Biological Morphodynamics.

Frontiers in systems biology Pub Date : 2022-09-01 Epub Date: 2022-09-09 DOI:10.3389/fsysb.2022.898858
Eric Mjolsness
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Abstract

Many emergent, non-fundamental models of complex systems can be described naturally by the temporal evolution of spatial structures with some nontrivial discretized topology, such as a graph with suitable parameter vectors labeling its vertices. For example, the cytoskeleton of a single cell, such as the cortical microtubule network in a plant cell or the actin filaments in a synapse, comprises many interconnected polymers whose topology is naturally graph-like and dynamic. The same can be said for cells connected dynamically in a developing tissue. There is a mathematical framework suitable for expressing such emergent dynamics, "stochastic parameterized graph grammars," composed of a collection of the graph- and parameter-altering rules, each of which has a time-evolution operator that suitably moves probability. These rule-level operators form an operator algebra, much like particle creation/annihilation operators or Lie group generators. Here, we present an explicit and constructive calculation, in terms of elementary basis operators and standard component notation, of what turns out to be a general combinatorial expression for the operator algebra that reduces products and, therefore, commutators of graph grammar rule operators to equivalent integer-weighted sums of such operators. We show how these results extend to "dynamical graph grammars," which include rules that bear local differential equation dynamics for some continuous-valued parameters. Commutators of such time-evolution operators have analytic uses, including deriving efficient simulation algorithms and approximations and estimating their errors. The resulting formalism is complementary to spatial models in the form of partial differential equations or stochastic reaction-diffusion processes. We discuss the potential application of this framework to the remodeling dynamics of the microtubule cytoskeleton in cortical microtubule networks relevant to plant development and of the actin cytoskeleton in, for example, a growing or shrinking synaptic spine head. Both cytoskeletal systems underlie biological morphodynamics.

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生物形态动力学中随机和动态图形文法规则算子结构换向关系的显式计算。
许多复杂系统的新出现的非基本模型,可以通过具有某种非离散拓扑结构的空间结构的时间演化来自然描述,例如具有适当参数向量标记顶点的图。例如,单个细胞的细胞骨架,如植物细胞中的皮层微管网络或突触中的肌动蛋白丝,由许多相互连接的聚合物组成,其拓扑结构自然是类似图的动态拓扑结构。发育中组织中动态连接的细胞也是如此。有一种数学框架适用于表达这种突发动态,即 "随机参数化图形语法",它由一系列图形和参数改变规则组成,其中每个规则都有一个时间演化算子,可以适当地移动概率。这些规则级算子构成了一个算子代数,很像粒子创造/湮灭算子或李群发生器。在这里,我们用基本基算子和标准成分符号,对算子代数的一般组合表达式进行了明确和建设性的计算,这种表达式可以将图语法规则算子的乘积和换元器还原为此类算子的等效整数加权和。我们展示了这些结果是如何扩展到 "动态图语法 "的,"动态图语法 "包括对某些连续值参数具有局部微分方程动力学的规则。这种时间演化算子的换元具有分析用途,包括推导出高效的模拟算法和近似值,以及估计它们的误差。由此产生的形式主义与偏微分方程或随机反应扩散过程形式的空间模型相辅相成。我们讨论了这一框架在与植物发育相关的皮层微管网络中的微管细胞骨架重塑动力学,以及在例如突触棘头的生长或收缩中的肌动蛋白细胞骨架重塑动力学中的潜在应用。这两种细胞骨架系统都是生物形态动力学的基础。
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