A comparative study of qualitative and quantitative dynamic models of biological regulatory networks
A comparative study of qualitative and quantitative dynamic models of biological regulatory networks
复制标题
生物调控网络定性与定量动态模型的比较研究
DOI：
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复制
发表时间：
2016
期刊：
影响因子：
--
通讯作者：
R. Albert
中科院分区：
文献类型：
--
作者：
A. Saadatpour;R. Albert
背景生物调控网络的数学建模提供了有价值的见解的基础系统的结构和动力学特性。虽然基于微分方程的动态模型提供了生物系统的定量信息，但依赖于组件之间的逻辑相互作用的定性模型提供了粗粒度的描述，对于其机械基础仍然不完全理解的系统非常有用。中间地面类的分段仿射微分方程模型被证明是翔实的动力学parameters.MethodsIn这项工作中，我们提供了这三种方法应用于几个生物调控网络图案的动态特性的比较系统的部分知识。具体来说，我们比较异步布尔，分段仿射和希尔型连续models.ResultsOur研究表明，而异步布尔模型的不动点观察连续希尔型和分段仿射models.ConclusionsOverall，定性模型可能会表现出不同的吸引子在一定的conditions.ConclusionsOverall，定量信息的知识有限的系统是合适的。另一方面，在实践中，使用定量模型可以提供有关定性模型中不存在的附加实值吸引子的详细信息。
BackgroundMathematical modeling of biological regulatory networks provides valuable insights into the structural and dynamical properties of the underlying systems. While dynamic models based on differential equations provide quantitative information on the biological systems, qualitative models that rely on the logical interactions among the components provide coarse-grained descriptions useful for systems whose mechanistic underpinnings remain incompletely understood. The middle ground class of piecewise affine differential equation models was proven informative for systems with partial knowledge of kinetic parameters.MethodsIn this work we provide a comparison of the dynamic characteristics of these three approaches applied on several biological regulatory network motifs. Specifically, we compare the attractors and state transitions in asynchronous Boolean, piecewise affine and Hill-type continuous models.ResultsOur study shows that while the fixed points of asynchronous Boolean models are observed in continuous Hill-type and piecewise affine models, these models may exhibit different attractors under certain conditions.ConclusionsOverall, qualitative models are suitable for systems with limited knowledge of quantitative information. On the other hand, when practical, using quantitative models can provide detailed information about additional real-valued attractors not present in the qualitative models.
DOI：
10.1073/pnas.88.16.7328
发表时间：
1991-08-01
影响因子：
11.1
作者：
TYSON, JJ
通讯作者：
TYSON, JJ
癌症基因组学中的单细胞分析。
DOI：
10.1016/j.tig.2015.07.003
发表时间：
2015-10
期刊：
Trends in genetics : TIG
影响因子：
--
作者：
Saadatpour A;Lai S;Guo G;Yuan GC
通讯作者：
Yuan GC
影响因子：
2
作者：
Albert, R;Othmer, HG
通讯作者：
Othmer, HG