Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram.
Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram.
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DOI：
10.1186/1752-0509-4-39
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发表时间：
2010-04-01
影响因子：
--
通讯作者：
Miyano S
中科院分区：
文献类型：
--
作者：
Li C;Nagasaki M;Saito A;Miyano S
随着通过模拟大规模生物网络获得的计算机数据的积累，一个新的研究兴趣正在出现，以阐明活生物体如何随着时间的推移在细胞中发挥作用。研究当前计算模型的动力学特征有助于更深入地理解复杂的细胞过程。这导致我们开发一种方法，利用模型的结构特性在所有的模拟时间步长。此外，用户友好的动态行为的概述可以被认为是在理解系统机制的变化提供了很大的帮助。提出了一种利用高级Petri网的时间过程仿真数据构造和分析活动状态转换图的新方法。我们的方法包括两个新的算法。第一个算法提取一系列的时间序列（称为时间序列），反映生物成分的动态，同时保留积极的数学品质。第二种方法创建一个由唯一的时间序列组成的ASTD。美洲培发协会向用户提供简明的信息，使他们能够掌握和跟踪关键的监管子网和/或网络如何随时间变化。我们的方法的适用性证明了在果蝇的昼夜节律的基本模型的分析。建立ASTD是将处理离散、连续和更复杂事件的混合模型转换为有限时变状态的有效手段。基于ASTD，可以应用各种分析方法来获得不仅是系统机制而且是动力学的新见解。
With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics.
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影响因子：
64.5
作者：
Price, JL;Blau, J;Young, MW
通讯作者：
Young, MW
影响因子：
1.6
作者：
Heiner, M;Koch, I;Will, R
通讯作者：
Will, R
影响因子：
3
作者：
Grafahrend-Belau E;Schreiber F;Heiner M;Sackmann A;Junker BH;Grunwald S;Speer A;Winder K;Koch I
通讯作者：
Koch I
影响因子：
--
作者：
Nagasaki, Masao;Saito, Ayumu;Miyano, Satoru
通讯作者：
Miyano, Satoru
影响因子：
5.8
作者：
Koch, I;Junker, BH;Heiner, M
通讯作者：
Heiner, M