论文标题

细胞生理组:在计算生理框架中我们需要什么来预测单细胞生物学?

The Cell Physiome: What do we need in a computational physiology framework for predicting single cell biology?

论文作者

Rajagopal, Vijay, Arumugam, Senthil, Hunter, Peter, Khadangi, Afshin, Chung, Joshua, Pan, Michael

论文摘要

现代生物学和生物医学正在经历大数据爆炸,需要先进的计算算法来提取对活细胞生理状态的机械见解。我们介绍了细胞生理学的动机:一种创建,共享和使用基于生物物理学的单细胞生理学计算模型的框架和方法。使用钙信号,生物能学和内体运输中的示例,我们强调了基于空间详细的,基于生物物理学的计算模型的需求,以发现细胞生物学基础的新机制。我们审查了迄今为止为创建细胞生理模型的进度和挑战。然后,我们引入键图作为创建细胞生理模型的一种有效方法,以整合化学,机械,电磁和热过程,同时保持质量和能量平衡。键图可增强细胞计算模型的模块化和可重复性。我们以期待的步骤结论,将有助于充分实现这一激动人心的机械生物医学数据科学领域。

Modern biology and biomedicine are undergoing a big-data explosion needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome: a framework and approach for creating, sharing, and using biophysics-based computational models of single cell physiology. Using examples in calcium signaling, bioenergetics, and endosomal trafficking, we highlight the need for spatially detailed, biophysics-based computational models to uncover new mechanisms underlying cell biology. We review progress and challenges to date towards creating cell physiome models. We then introduce bond graphs as an efficient way to create cell physiome models that integrate chemical, mechanical, electromagnetic, and thermal processes while maintaining mass and energy balance. Bond graphs enhance modularization and re-usability of computational models of cells at scale. We conclude with a look forward into steps that will help fully realize this exciting new field of mechanistic biomedical data science.

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