论文标题
罢工 - 戈尔德4.0：对结构可识别性和可观察性的用户友好，有效分析
STRIKE-GOLDD 4.0: user-friendly, efficient analysis of structural identifiability and observability
论文作者
论文摘要
结构可识别性和可观察性是系统生物学模型的理想特性。在过去的几十年中，已经开发了许多软件工具箱进行分析。 Strike-Goldd是一种通常适用的工具，可以分析具有未知输入的非线性非理性ode模型。但是，这种通用性的代价是比其他工具低的计算效率。在这里，我们介绍Strike-Goldd 4.0，其中包括一种新算法，ProbObstest，专门设计用于分析有理模型的算法。当应用于计算昂贵的模型时，ProbObstest的速度明显快于工具箱的旧版本中的Fispo算法快得多。两种算法的重要特征是它们能够分析输入未知的模型。因此，它们在同一工具箱中的共存提供了一般适用性和计算效率的组合。 Strike-Goldd 4.0被实现为具有用户友好的图形接口的免费开源MATLAB工具箱。它可在GPLV3许可证下获得，可以从https://github.com/afvillaverde/strike-goldd上从Github下载。
Structural identifiability and observability are desirable properties of systems biology models. Many software toolboxes have been developed for their analysis in the last decades. STRIKE-GOLDD is a generally applicable tool that can analyse non-linear, non-rational ODE models with unknown inputs. However, this generality comes at the expense of a lower computational efficiency than other tools. Here we present STRIKE-GOLDD 4.0, which includes a new algorithm, ProbObsTest, specifically designed for the analysis of rational models. ProbObsTest is significantly faster than the FISPO algorithm - which was already available in older versions of the toolbox - when applied to computationally expensive models. An important feature of both algorithms is their ability to analyse models with unknown inputs. Thus, their coexistence in the same toolbox provides a combination of general applicability and computational efficiency. STRIKE-GOLDD 4.0 is implemented as a free and open-source Matlab toolbox with a user-friendly graphical interface. It is available under a GPLv3 license and it can be downloaded from GitHub at https://github.com/afvillaverde/strike-goldd.
