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Experimental and computational methods for the analysis and modeling of signaling networks

机译：用于信令网络分析和建模的实验和计算方法

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摘要

External cues are processed and integrated by signal transduction networks that drive appropriate cellular responses. Characterizing these programs, as well as how their deregulation leads to disease, is crucial for our understanding of cell biology. The past ten years have witnessed a gradual increase in the number of molecular parameters that can be simultaneously measured in a sample. Moreover our capacity to handle multiple samples in parallel has expanded, thus allowing a deeper profiling of cellular states under diverse experimental conditions. These technological advances have been complemented by the development of computational methods aimed at mining, analyzing and modeling these data. In this review we give a general overview of the most important experimental and computational techniques used in the field and describe several interesting application of these methodologies. We conclude by highlighting the issues that we think will keep researchers in the field busy in the next few years.
机译：外部提示由驱动适当细胞反应的信号转导网络处理和整合。这些程序的特征以及它们的放松管制如何导致疾病，对于我们对细胞生物学的理解至关重要。在过去的十年中，可以同时测量样品中的分子参数数量逐渐增加。此外，我们并行处理多个样品的能力得到了扩展，因此可以在各种实验条件下对细胞状态进行更深层次的分析。这些技术进步已被旨在挖掘，分析和建模这些数据的计算方法的发展所补充。在这篇综述中，我们对本领域中使用的最重要的实验和计算技术进行了概述，并描述了这些方法的一些有趣的应用。最后，我们着重指出我们认为将在未来几年中使该领域的研究人员忙碌的问题。

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