Li Min, Li Dongyan, Tang Yu, Wu Fangxiang, Wang Jianxin
School of Information Science and Engineering, Central South University, Changsha 410083, China.
School of software, Central South University, Changsha 410083, China.
Int J Mol Sci. 2017 Aug 31;18(9):1880. doi: 10.3390/ijms18091880.
Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.
如今，生物网络的聚类分析已成为识别功能模块以及预测蛋白质复合物和网络生物标志物的最重要方法之一。此外，聚类结果的可视化对于展示生物网络的结构至关重要。在此，我们展示了CytoCluster，这是一个Cytoscape插件，集成了六种聚类算法，即HC-PIN（蛋白质相互作用网络中的层次聚类算法）、OH-PIN（识别蛋白质相互作用网络中的重叠和层次模块）、IPCA（识别蛋白质复合物算法）、ClusterONE（基于重叠邻域扩展的聚类）、DCU（基于不确定图模型检测复合物）、IPC-MCE（基于最大复合物扩展识别蛋白质复合物）以及BinGO（生物网络基因本体）功能。用户可以根据自身需求选择不同的聚类算法。这六种聚类算法的主要功能是检测蛋白质复合物或功能模块。此外，BinGO用于确定哪些基因本体（GO）类别在一组基因或生物网络的子图中具有统计学上的过度代表性。CytoCluster可以轻松扩展，以便能够向此插件添加更多聚类算法和功能。自2013年7月创建以来，CytoCluster在Cytoscape应用商店中的下载量已超过9700次，并且已应用于不同生物网络的分析。可从http://apps.cytoscape.org/apps/cytocluster获取CytoCluster。
