Dynamic models formulated as ordinary differential equations can provide information about the mechanistic and causal interactions in biological systems to guide targeted interventions and to design further experiments. Inaccurate knowledge about the structure, functional form and parameters of interactions is a major obstacle to mechanistic modeling. A further challenge is the open nature of biological systems which receive unknown inputs from their environment. The R-package SEEDS implements two recently developed algorithms to infer structural model errors and unknown inputs from output measurements. This information can facilitate efficient model recalibration as well as experimental design in the case of misfits between the initial model and data.

中文翻译：

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SEEDS：动态系统生物学的结构模型错误和未知输入的数据驱动推理

制定为常微分方程的动态模型可以提供有关生物系统中机械和因果相互作用的信息，以指导有针对性的干预和设计进一步的实验。关于相互作用的结构、功能形式和参数的不准确知识是机械建模的主要障碍。另一个挑战是从环境中接收未知输入的生物系统的开放性。R-package SEEDS 实现了两种最近开发的算法，以从输出测量中推断结构模型错误和未知输入。在初始模型和数据不匹配的情况下，此信息可以促进有效的模型重新校准以及实验设计。