...
首页> 外文期刊>Royal Society Open Science >Scalable population-level modelling of biological cells incorporating mechanics and kinetics in continuous time
【24h】

Scalable population-level modelling of biological cells incorporating mechanics and kinetics in continuous time

机译:在连续时间内结合力学和动力学的生物细胞可扩展的种群级建模

获取原文
           

摘要

The processes taking place inside the living cell are now understood to the point where predictive computational models can be used to gain detailed understanding of important biological phenomena. A key challenge is to extrapolate this detailed knowledge of the individual cell to be able to explain at the population level how cells interact and respond with each other and their environment. In particular, the goal is to understand how organisms develop, maintain and repair functional tissues and organs. In this paper, we propose a novel computational framework for modelling populations of interacting cells. Our framework incorporates mechanistic, constitutive descriptions of biomechanical properties of the cell population, and uses a coarse-graining approach to derive individual rate laws that enable propagation of the population through time. Thanks to its multiscale nature, the resulting simulation algorithm is extremely scalable and highly efficient. As highlighted in our computational examples, the framework is also very flexible and may straightforwardly be coupled with continuous-time descriptions of biochemical signalling within, and between, individual cells.
机译:现在已经了解了活细胞内部发生的过程,可以使用预测性计算模型来获得对重要生物学现象的详细了解。一个关键的挑战是推断单个细胞的详细知识,以便能够在群体水平上解释细胞如何相互作用以及彼此之间及其环境之间的反应。特别是,目标是了解生物体如何发育,维持和修复功能性组织和器官。在本文中,我们提出了一种新型的计算框架,用于建模相互作用细胞的种群。我们的框架结合了细胞群体生物力学特性的机械性,本构性描述,并使用粗粒度方法来得出使速率随时间传播的个体速率定律。由于具有多尺度特性,因此生成的仿真算法具有极高的可扩展性和高效性。如我们的计算示例中突出显示的那样,该框架也非常灵活,可以直接与单个细胞内以及细胞之间生化信号的连续时间描述结合起来。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号