Abstract
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.
Highlights
The network concept is widely used to analyze and predict the dynamics of a complex system [1]
When we talk about the networks, the complex system is perceived as a set of interacting elements, which are bound together by links
We introduce CytoKavosh as the first network motif finder plug-in for Cytoscape, which uses all Kavosh features and strengthen the studies of finding network motifs based on Milo [1]
Summary
The network concept is widely used to analyze and predict the dynamics of a complex system [1]. Computational tools help biologists through this difficult study An understanding of these networks is essential to make the biological sense of much of the complex data that is being generated [2]. Different methods and stand-alone tools have been developed for analyzing the network motifs: Mfinder [5], MAVisto [6], NeMoFinder [7], Grochow-Kellis [8], Color-coding approach [9], G-Tries [10], FANMOD [11], Kavosh [12] and MODA [13]. FANMOD algorithm is one of the best among others, in regard to the computational time It can handle sub-graphs, consisting of a maximum of eight vertices. The Kavosh plug-in is the best tool, according to the time and memory usage, among all and has no limitation in the size of motifs studied by this program [12]. The results of CytoKavosh can be used in-line with other analysis tools in the integrated software to achieve the desired goals
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