Wang Shuqiang, Shen Yanyan, Shi Changhong, Wang Tao, Wei Zhiming, Li Hanxiong
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518000, China ; Department of Orthopaedics and Traumatology, University of Hong Kong, Hong Kong.
Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Hong Kong.
ScientificWorldJournal. 2014;2014:625754. doi: 10.1155/2014/625754. Epub 2014 Jun 5.
Reliable information processing in cells requires high sensitivity to changes in the input signal but low sensitivity to random fluctuations in the transmitted signal. There are often many alternative biological circuits qualifying for this biological function. Distinguishing theses biological models and finding the most suitable one are essential, as such model ranking, by experimental evidence, will help to judge the support of the working hypotheses forming each model. Here, we employ the approximate Bayesian computation (ABC) method based on sequential Monte Carlo (SMC) to search for biological circuits that can maintain signaling sensitivity while minimizing noise propagation, focusing on cases where the noise is characterized by rapid fluctuations. By systematically analyzing three-component circuits, we rank these biological circuits and identify three-basic-biological-motif buffering noise while maintaining sensitivity to long-term changes in input signals. We discuss in detail a particular implementation in control of nutrient homeostasis in yeast. The principal component analysis of the posterior provides insight into the nature of the reaction between nodes.
细胞中可靠的信息处理需要对输入信号的变化具有高灵敏度，但对传输信号中的随机波动具有低灵敏度。通常有许多符合这种生物学功能的替代生物电路。区分这些生物学模型并找到最合适的模型至关重要，因为通过实验证据进行这种模型排序将有助于判断形成每个模型的工作假设的支持情况。在这里，我们采用基于序贯蒙特卡罗（SMC）的近似贝叶斯计算（ABC）方法来搜索能够在最小化噪声传播的同时保持信号灵敏度的生物电路，重点关注噪声以快速波动为特征的情况。通过系统地分析三组分电路，我们对这些生物电路进行排序，并识别出在保持对输入信号长期变化的灵敏度的同时缓冲噪声的三种基本生物基序。我们详细讨论了酵母中营养稳态控制的一种特定实现。后验的主成分分析提供了对节点间反应性质的洞察。
