MacNamara Aidan, Henriques David, Saez-Rodriguez Julio
EMBL Outstation-European Bioinformatics Institute, Cambridge, UK.
Methods Mol Biol. 2013;1021:89-105. doi: 10.1007/978-1-62703-450-0_5.
In the last 30 years, many of the mechanisms behind signal transduction, the process by which the cell takes extracellular signals as an input and converts them to a specific cellular phenotype, have been experimentally determined. With these discoveries, however, has come the realization that the architecture of signal transduction, the signaling network, is incredibly complex. Although the main pathways between receptor and output are well-known, there is a complex net of regulatory features that include crosstalk between different pathways, spatial and temporal effects, and positive and negative feedbacks. Hence, modeling approaches have been used to try and unravel some of these complexities. We use the mitogen-activated protein kinase cascade to illustrate chemical kinetic and logic approaches to modeling signaling networks. By using a common well-known model, we illustrate here the assumptions and level of detail behind each modeling approach, which serves as an introduction to the more detailed discussions of each in the accompanying chapters in this book.
在过去30年里，信号转导背后的许多机制已通过实验确定，信号转导是细胞将细胞外信号作为输入并将其转化为特定细胞表型的过程。然而，随着这些发现的出现，人们也意识到信号转导的架构，即信号网络，极其复杂。尽管受体与输出之间的主要途径已为人熟知，但存在一个复杂的调节特征网络，包括不同途径之间的串扰、时空效应以及正负反馈。因此，已采用建模方法来试图揭示其中一些复杂性。我们使用丝裂原活化蛋白激酶级联反应来说明对信号网络进行建模的化学动力学和逻辑方法。通过使用一个常见的知名模型，我们在此阐述每种建模方法背后的假设和细节程度，这可作为本书后续章节对每种方法更详细讨论的引言。
