Dynamic mechanistic models, that is, those that can simulate behavior over time courses, are a cornerstone of molecular systems biology. They are being used to model molecular mechanisms with varying degrees of granularity-from elementary reactions to causal links-and to describe these systems by various dynamic mathematical frameworks, such as Boolean networks or systems of differential equations. The models can be based exclusively on experimental data, or on prior knowledge of the underlying biological processes. The latter are typically generic, but can be adapted to a certain context, such as a particular cell type, after training with context-specific data. Dynamic mechanistic models that are based on biological knowledge have great potential for modeling specific systems, because they require less data for training to provide biological insight in particular into causal mechanisms, and to extrapolate to scenarios that are outside the conditions they have been trained on.

中文翻译：

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用于个性化治疗的个性化信号模型。


动态机制模型，即那些可以模拟随时间变化的行为的模型，是分子系统生物学的基石。它们被用来模拟不同粒度的分子机制（从基本反应到因果关系），并通过各种动态数学框架（例如布尔网络或微分方程系统）描述这些系统。这些模型可以完全基于实验数据，或基于潜在生物过程的先验知识。后者通常是通用的，但在使用特定于上下文的数据进行训练后可以适应特定的上下文，例如特定的细胞类型。基于生物学知识的动态机制模型在对特定系统进行建模方面具有巨大潜力，因为它们需要较少的数据进行训练，以提供生物学洞察力，特别是因果机制，并推断出超出其训练条件的场景。