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Computational modeling of cellular signaling processes embedded into dynamic spatial contexts

机译:嵌入动态空间环境的细胞信号传导过程的计算模型

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Cellular signaling processes depend on spatiotemporal distributions of molecular components. Multicolor, high-resolution microscopy permits detailed assessment of such distributions, providing input for fine-grained computational models that explore mechanisms governing dynamic assembly of multimolecular complexes and their role in shaping cellular behavior. However, it is challenging to incorporate into such models both complex molecular reaction cascades and the spatial localization of signaling components in dynamic cellular morphologies. Here we introduce an approach to address these challenges by automatically generating computational representations of complex reaction networks based on simple bimolecular interaction rules embedded into detailed, adaptive models of cellular morphology. Using examples of receptor-mediated cellular adhesion and signal-induced localized mitogen-activated protein kinase (MAPK) activation in yeast, we illustrate the capacity of this simulation technique to provide insights into cell biological processes. The modeling algorithms, implemented in a new version of the Simmune toolset, are accessible through intuitive graphical interfaces and programming libraries.
机译:细胞信号传导过程取决于分子成分的时空分布。多色高分辨率显微镜可以对这种分布进行详细评估,从而为细粒度的计算模型提供输入,这些模型探索了控制多分子复合物动态组装的机制及其在塑造细胞行为中的作用。然而,将复杂的分子反应级联和动态细胞形态中信号成分的空间定位结合到这样的模型中具有挑战性。在这里,我们介绍了一种方法,这些方法通过基于简单的双分子相互作用规则自动生成复杂反应网络的计算表示法来解决这些挑战,这些规则嵌入到详细的自适应细胞形态模型中。使用受体介导的细胞粘附和酵母中信号诱导的局部有丝分裂原激活的蛋白激酶(MAPK)活化的例子,我们说明了这种模拟技术的能力,可提供对细胞生物学过程的见解。通过直观的图形界面和编程库可以访问在新版本的Simmune工具集中实现的建模算法。

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