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首页> 外文会议>3rd international conference on bioinformatics and computational biology 2011 >Modeling and Simulation of Steroid Hormone Biosynthesis and Disease State using Petri Nets
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Modeling and Simulation of Steroid Hormone Biosynthesis and Disease State using Petri Nets

机译：用Petri网建模和模拟类固醇激素的合成和疾病状态

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摘要

The use of a Petri net (PN) to model biochemical pathways provides a powerful analytical tool that can lead to a better understanding of the specific reactions and their order within complex processes. PNs can be used to model biological processes on many levels. Qualitative Petri nets, like a stochastic Petri net (SPN), can answer quite a few questions about biological processes concerning their reachability, structure, and topology. In this paper, two different Petri net simulation tools, i.e., HPSim and YASPER and a SPN modeling were used to demonstrate and analyze disease states of Steroid Hormone Biosynthesis (SHB). Petri nets (PN) of the SHB process were created to compare the differences between the processes of adrenal glands and gonads of males and females expressing different forms of congenital adrenal hyperplasia (CAH), 5a Reductase Deficiency, Aromatase Excess, Aromatase Deficiency and a non-expressing state. By reference to hormone levels from blood analysis of males and females not expressing disease states, we establish non-diseased hormone levels as a baseline. Since each steroid begins the biosynthesis process as a cholesterol molecule, and manifestation of a steroid implies reaction with specific enzymes, the process directly resembles a Markov chain, analogous to a state machine PN, for example, adjusting the PN's interaction probabilities to match the production ratios arrived from the blood sample data creates a probability map demonstrating how the steroids are most probably formed in an individual not expressing CAH. Each disease state is defined by a deficiency or excess of a production enzyme, mathematically expressible as an altered probability of interaction with the steroid molecule.
机译：使用Petri网（PN）对生化途径进行建模可提供强大的分析工具，可帮助您更好地理解特定反应及其在复杂过程中的顺序。 PNs可用于在许多层面上对生物过程进行建模。与随机Petri网（SPN）一样，定性Petri网可以回答有关其可及性，结构和拓扑的生物学过程的很多问题。本文使用两种不同的Petri网仿真工具HPSim和YASPER以及SPN建模来演示和分析类固醇激素生物合成（SHB）的疾病状态。建立了SHB进程的Petri网（PN），以比较表达不同形式的先天性肾上腺皮质增生（CAH），5a还原酶缺乏症，芳香酶过量，芳香酶缺乏症和非肾上腺的男性和女性的肾上腺和性腺过程之间的差异表达状态。通过参考未表达疾病状态的男性和女性血液分析中的激素水平，我们将未患病激素水平作为基线。由于每个类固醇都以胆固醇分子的形式开始生物合成过程，并且类固醇的出现暗示着与特定酶的反应，因此该过程直接类似于马尔可夫链，类似于状态机PN，例如，调整PN的相互作用概率以匹配生产过程。从血液样本数据得出的比率会创建一个概率图，该图表明类固醇是如何在不表达CAH的个体中形成的。每种疾病状态均由生产酶的缺乏或过量定义，该酶在数学上可表达为与类固醇分子相互作用的概率改变。

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