Department of Computer Science, National Tsing Hua University, Hsinchu, 30013 Taiwan, ROC.
BMC Bioinformatics. 2011 Feb 15;12 Suppl 1(Suppl 1):S17. doi: 10.1186/1471-2105-12-S1-S17.
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 the subsequent 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.
In present study, we employed a genetic algorithm-based Boolean model to represent NF-κB 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.
We designed an effective algorithm to elucidate the process of immune response using comprehensive knowledge about network structure and limited experimental data on dynamic responses. This approach can potentially be implemented for large-scale analysis on cellular processes and organism behaviors.
信号转导是细胞将外部刺激传递到细胞内引发生化反应的主要机制。理解外部刺激与相应的细胞反应之间的关系,以及对下游基因的后续影响,是系统生物学的主要挑战。因此,需要采用一种系统的方法将实验数据和定性知识整合起来,以确定环境刺激的生理后果。
在本研究中,我们采用基于遗传算法的布尔模型来表示 NF-κB 信号通路。我们能够捕捉到反馈和串扰的特征,从而加深对急性和慢性炎症反应的理解。确定了影响反应动力学的关键网络组件。
我们设计了一种有效的算法,利用关于网络结构的综合知识和关于动态反应的有限实验数据来阐明免疫反应的过程。这种方法可以潜在地用于对细胞过程和生物体行为进行大规模分析。