Kuntal Bhusan K, Dutta Anirban, Mande Sharmila S
Bio-Sciences R&D Division, TCS Research, Tata Consultancy Services Ltd., 54-B, Hadapsar Industrial Estate, Pune, 411 013, Maharashtra, India.
BMC Bioinformatics. 2016 Apr 26;17(1):185. doi: 10.1186/s12859-016-1013-x.
Network visualization and analysis tools aid in better understanding of complex biological systems. Furthermore, to understand the differences in behaviour of system(s) under various environmental conditions (e.g. stress, infection), comparing multiple networks becomes necessary. Such comparisons between multiple networks may help in asserting causation and in identifying key components of the studied biological system(s). Although many available network comparison methods exist, which employ techniques like network alignment and querying to compute pair-wise similarity between selected networks, most of them have limited features with respect to interactive visual comparison of multiple networks.
In this paper, we present CompNet - a graphical user interface based network comparison tool, which allows visual comparison of multiple networks based on various network metrics. CompNet allows interactive visualization of the union, intersection and/or complement regions of a selected set of networks. Different visualization features (e.g. pie-nodes, edge-pie matrix, etc.) aid in easy identification of the key nodes/interactions and their significance across the compared networks. The tool also allows one to perform network comparisons on the basis of neighbourhood architecture of constituent nodes and community compositions, a feature particularly useful while analyzing biological networks. To demonstrate the utility of CompNet, we have compared a (time-series) human gene-expression dataset, post-infection by two strains of Mycobacterium tuberculosis, overlaid on the human protein-protein interaction network. Using various functionalities of CompNet not only allowed us to comprehend changes in interaction patterns over the course of infection, but also helped in inferring the probable fates of the host cells upon infection by the two strains.
CompNet is expected to be a valuable visual data mining tool and is freely available for academic use from http://metagenomics.atc.tcs.com/compnet/ or http://121.241.184.233/compnet/.
网络可视化和分析工具有助于更好地理解复杂的生物系统。此外,为了了解系统在各种环境条件(如压力、感染)下行为的差异,比较多个网络变得很有必要。多个网络之间的这种比较可能有助于确定因果关系,并识别所研究生物系统的关键组成部分。尽管存在许多可用的网络比较方法,这些方法采用网络比对和查询等技术来计算所选网络之间的成对相似度,但它们中的大多数在多个网络的交互式可视化比较方面功能有限。
在本文中,我们展示了CompNet——一种基于图形用户界面的网络比较工具,它允许基于各种网络指标对多个网络进行可视化比较。CompNet允许对所选网络集的并集、交集和/或补集区域进行交互式可视化。不同的可视化特征(如饼状节点、边饼矩阵等)有助于轻松识别关键节点/相互作用及其在比较网络中的重要性。该工具还允许用户基于组成节点的邻域结构和社区组成进行网络比较,这一功能在分析生物网络时特别有用。为了证明CompNet的实用性,我们比较了一个(时间序列)人类基因表达数据集,该数据集是在感染两种结核分枝杆菌菌株后叠加在人类蛋白质-蛋白质相互作用网络上的。使用CompNet的各种功能不仅使我们能够理解感染过程中相互作用模式的变化,还有助于推断宿主细胞在被这两种菌株感染后的可能命运。
CompNet有望成为一个有价值的可视化数据挖掘工具,可从http://metagenomics.atc.tcs.com/compnet/ 或http://121.241.184.233/compnet/免费获取用于学术用途。