QSSPN: dynamic simulation of molecular interaction networks describing gene regulation, signalling and whole-cell metabolism in human cells.
QSSPN: dynamic simulation of molecular interaction networks describing gene regulation, signalling and whole-cell metabolism in human cells.
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DOI：
10.1093/bioinformatics/btt552
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发表时间：
2013-12-15
期刊：
影响因子：
--
通讯作者：
Kierzek AM
中科院分区：
文献类型：
--
作者：
Fisher CP;Plant NJ;Moore JB;Kierzek AM
动机：基因组规模的分子相互作用网络的动态模拟将使基因-表型关系的机制预测成为可能。尽管数量生物学取得了进展，但全细胞模型的完全参数化仍是不可能的。能够利用现有定性数据的仿真方法需要通过建模和实验验证的迭代过程来开发动态全细胞模型。结果：我们建立了准稳态的Petri网(QSSPN)，这是一种结合了Petri网和基于约束的分析的新方法，用于预测基因调控、信号转导和全细胞代谢的定性模型中定性动态行为的可行性。我们首次提出了动态模拟，包括调节机制和人类细胞基因组规模的代谢网络，以人类肝细胞中的胆汁酸稳态为例进行研究。QSSPN模拟再现了实验确定的定性动态行为，并允许对基因型-表型关系进行机械分析。可获得性和可实施性：用C++实现的模型和模拟软件可在补充材料和http://sysbio3.fhms.surrey.ac.uk/qsspn/.上获得联系人：a.kierzek@surrey.ac.uk补充信息：补充数据可在BioInformation Online上获得。
Motivation: Dynamic simulation of genome-scale molecular interaction networks will enable the mechanistic prediction of genotype–phenotype relationships. Despite advances in quantitative biology, full parameterization of whole-cell models is not yet possible. Simulation methods capable of using available qualitative data are required to develop dynamic whole-cell models through an iterative process of modelling and experimental validation. Results: We formulate quasi-steady state Petri nets (QSSPN), a novel method integrating Petri nets and constraint-based analysis to predict the feasibility of qualitative dynamic behaviours in qualitative models of gene regulation, signalling and whole-cell metabolism. We present the first dynamic simulations including regulatory mechanisms and a genome-scale metabolic network in human cell, using bile acid homeostasis in human hepatocytes as a case study. QSSPN simulations reproduce experimentally determined qualitative dynamic behaviours and permit mechanistic analysis of genotype–phenotype relationships. Availability and implementation: The model and simulation software implemented in C++ are available in supplementary material and at http://sysbio3.fhms.surrey.ac.uk/qsspn/. Contact: a.kierzek@surrey.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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