Millán Pablo Porras
EMBL Outstation-European Bioinformatics Institute, Cambridge, UK.
Methods Mol Biol. 2013;1021:63-88. doi: 10.1007/978-1-62703-450-0_4.
The study of the interactome-the totality of the protein-protein interactions taking place in a cell-has experienced an enormous growth in the last few years. Biological networks representation and analysis has become an everyday tool for many biologists and bioinformatics, as these interaction graphs allow us to map and characterize signaling pathways and predict the function of unknown proteins. However, given the size and complexity of interactome datasets, extracting meaningful information from interaction networks can be a daunting task. Many different tools and approaches can be used to build, represent, and analyze biological networks. In this chapter, we will use a practical example to guide novice users through this process. We will be making use of the popular open source tool Cytoscape and of other resources such as : the PSICQUIC client to access several protein interaction repositories and the BiNGO plugin to perform GO enrichment analysis of the resulting network.
对细胞中发生的蛋白质-蛋白质相互作用的整体——相互作用组的研究在过去几年中经历了巨大的发展。生物网络的表示和分析已成为许多生物学家和生物信息学工作者日常使用的工具，因为这些相互作用图使我们能够绘制和表征信号通路，并预测未知蛋白质的功能。然而，鉴于相互作用组数据集的规模和复杂性，从相互作用网络中提取有意义的信息可能是一项艰巨的任务。许多不同的工具和方法可用于构建、表示和分析生物网络。在本章中，我们将通过一个实际例子引导新手用户完成这个过程。我们将使用流行的开源工具Cytoscape以及其他资源，如：用于访问多个蛋白质相互作用知识库的PSICQUIC客户端，以及用于对所得网络进行基因本体（GO）富集分析的BiNGO插件。
