Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
PLoS One. 2012;7(8):e43287. doi: 10.1371/journal.pone.0043287. Epub 2012 Aug 29.
Network motifs are small connected sub-graphs that have recently gathered much attention to discover structural behaviors of large and complex networks. Finding motifs with any size is one of the most important problems in complex and large networks. It needs fast and reliable algorithms and tools for achieving this purpose. CytoKavosh is one of the best choices for finding motifs with any given size in any complex network. It relies on a fast algorithm, Kavosh, which makes it faster than other existing tools. Kavosh algorithm applies some well known algorithmic features and includes tricky aspects, which make it an efficient algorithm in this field. CytoKavosh is a Cytoscape plug-in which supports us in finding motifs of given size in a network that is formerly loaded into the Cytoscape work-space (directed or undirected). High performance of CytoKavosh is achieved by dynamically linking highly optimized functions of Kavosh's C++ to the Cytoscape Java program, which makes this plug-in suitable for analyzing large biological networks. Some significant attributes of CytoKavosh is efficiency in time usage and memory and having no limitation related to the implementation in motif size. CytoKavosh is implemented in a visual environment Cytoscape that is convenient for the users to interact and create visual options to analyze the structural behavior of a network. This plug-in can work on any given network and is very simple to use and generates graphical results of discovered motifs with any required details. There is no specific Cytoscape plug-in, specific for finding the network motifs, based on original concept. So, we have introduced for the first time, CytoKavosh as the first plug-in, and we hope that this plug-in can be improved to cover other options to make it the best motif-analyzing tool.
网络基元是最近备受关注的小连接子图，用于发现大型复杂网络的结构行为。寻找任何大小的基元是复杂和大型网络中最重要的问题之一。这需要快速可靠的算法和工具来实现这一目标。CytoKavosh 是在任何复杂网络中查找任何给定大小的基元的最佳选择之一。它依赖于一种快速算法 Kavosh，使其比其他现有工具更快。Kavosh 算法应用了一些知名的算法特性，并包含了一些棘手的方面，使其成为该领域的高效算法。CytoKavosh 是 Cytoscape 的一个插件，支持在 Cytoscape 工作空间中（有向或无向）查找给定大小的网络基元。CytoKavosh 的高性能是通过将 Kavosh 的 C++高度优化的函数动态链接到 Cytoscape Java 程序来实现的，这使得这个插件适合分析大型生物网络。CytoKavosh 的一些重要属性是在时间使用和内存方面的高效性，并且在基元大小的实现方面没有限制。CytoKavosh 是在可视化环境 Cytoscape 中实现的，方便用户交互并创建可视化选项来分析网络的结构行为。这个插件可以在任何给定的网络上运行，非常易于使用，并生成带有任何所需详细信息的发现基元的图形结果。目前没有基于原始概念的专门用于寻找网络基元的 Cytoscape 插件。因此，我们首次引入了 CytoKavosh 作为第一个插件，我们希望这个插件能够得到改进，以涵盖其他选项，使其成为最佳的基元分析工具。
