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A genetic algorithm-based boolean delay model of intracellular signal transduction in inflammation

机译:基于遗传算法的炎症细胞内信号转导的布尔延迟模型

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Background: Signal transduction is the major mechanism through which cells transmit external stimuli to evoke intracellular biochemical responses. Understanding relationship between external stimuli and corresponding cellular responses, as well as thesubsequent effects on downstream genes, is a major challenge in systems biology. Thus, a systematic approach to integrate experimental data and qualitative knowledge to identify the physiological consequences of environmental stimuli is needed. Results:In present study, we employed a genetic algorithm-based Boolean model to represent NF-kB signaling pathway. We were able to capture feedback and crosstalk characteristics to enhance our understanding on the acute and chronic inflammatory response. Key network components affecting the response dynamics were identified. Conclusions: We designed an effective algorithm to elucidate the process of immune response using comprehensive knowledge about network structure and limited experimental data on dynamicresponses. This approach can potentially be implemented for large-scale analysis on cellular processes and organism behaviors.
机译:背景:信号转导是细胞传递外部刺激以引起细胞内生物化学反应的主要机制。了解外部刺激与相应细胞反应之间的关系,以及对下游基因的对照效应,是系统生物学的主要挑战。因此,需要一种整合实验数据和定性知识来识别环境刺激的生理后果的系统方法。结果:在目前的研究中,我们采用了一种基于遗传算法的布尔模型来表示NF-KB信号通路。我们能够捕获反馈和串扰特征,以增强我们对急性和慢性炎症反应的理解。确定了影响响应动态的关键网组件。结论:我们设计了一种有效的算法,以阐明使用关于网络结构的全面知识和关于动态信徒的有限实验数据的免疫应答过程。这种方法可以用于对细胞过程和生物行为的大规模分析来实现。

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