Guo Xin, Hartemink Alexander J
Department of Computer Science, Duke University, Durham, NC 27708-0129, USA.
Bioinformatics. 2009 Jun 15;25(12):i240-6. doi: 10.1093/bioinformatics/btp202.
Recent advances in high-throughput experimental techniques have yielded a large amount of data on protein-protein interactions (PPIs). Since these interactions can be organized into networks, and since separate PPI networks can be constructed for different species, a natural research direction is the comparative analysis of such networks across species in order to detect conserved functional modules. This is the task of network alignment.
Most conventional network alignment algorithms adopt a node-then-edge-alignment paradigm: they first identify homologous proteins across networks and then consider interactions among them to construct network alignments. In this study, we propose an alternative direct-edge-alignment paradigm. Specifically, instead of explicit identification of homologous proteins, we directly infer plausibly alignable PPIs across species by comparing conservation of their constituent domain interactions. We apply our approach to detect conserved protein complexes in yeast-fly and yeast-worm PPI networks, and show that our approach outperforms two recent approaches in most alignment performance metrics.
Supplementary material and source code can be found at http://www.cs.duke.edu/ approximately amink/.
高通量实验技术的最新进展产生了大量关于蛋白质-蛋白质相互作用（PPI）的数据。由于这些相互作用可以组织成网络，并且由于可以为不同物种构建单独的PPI网络，一个自然的研究方向是对跨物种的此类网络进行比较分析，以检测保守的功能模块。这就是网络比对的任务。
大多数传统的网络比对算法采用先节点后边的比对范式：它们首先识别跨网络的同源蛋白质，然后考虑它们之间的相互作用来构建网络比对。在本研究中，我们提出了一种替代的直接边比对范式。具体而言，我们不是明确识别同源蛋白质，而是通过比较其组成域相互作用的保守性，直接推断跨物种的可能可比对的PPI。我们将我们的方法应用于检测酵母-果蝇和酵母-线虫PPI网络中的保守蛋白质复合物，并表明我们的方法在大多数比对性能指标上优于最近的两种方法。
补充材料和源代码可在http://www.cs.duke.edu/ approximately amink/上找到。
