Centrality exploration software tools | Protein interaction data analysis
Here, we surveyed bioinformatics software tools for network centrality inference. The elucidation of whole-cell regulatory, metabolic, interaction and other biological networks generates the need for a meaningful ranking of network elements. Centrality analysis ranks network elements according to their importance within the network structure and different centrality measures focus on different importance concepts. Central elements of biological networks have been found to be, for example, essential for viability.
Aims to create a sustainable software and technical ecosystem, driven by a large international open-source community, who shares common interests in networks and complex systems. Gephi is a leading visualization and exploration software for all kinds of graphs and networks. It provides easy and broad access to network data and allows for spatializing, filtering, navigating, manipulating and clustering.
Allows comprehensive network topology analysis. NetworkAnalyzer is a plugin of Cytoscape. The software performs a comprehensive analysis of network topologies without requiring advanced knowledge in graph theory or programming expertise. It supports the characterization of molecular networks in terms of scale-free and small-world properties, modularity and hierarchical structure, the identification of important network nodes and edges based on topological parameters and the comparison of networks with regard to their topology.
Uses for the analysis of social network data. UCINET is menu-driven Windows program that implements a diverse collection of network analysis techniques, in addition to traditional statistical procedures and data management facilities. It can read and write a multitude of differently formatted text files, as well as Excel files. In addition, this package has strong matrix analysis routines, such as matrix algebra and multivariate statistics.
Uses the MSPaint networks. NodeXL Basic is a free, open-source template for Microsoft Excel 2007, 2010, 2013 and 2016 that makes it easy to explore network graphs. With NodeXL, user can enter a network edge list in a worksheet, click a button and see its graph, all in the familiar environment of the Excel window. The pro version offers additional features that extend NodeXL Basic, providing easy access to social media network data streams, advanced network metrics, and text and sentiment analysis, and powerful report generation. NodeXL Pro can create insights into social media streams with just a few clicks.
A Cytoscape plug-in for calculating network centralities with numerical and graphical output. CentiScaPe computes several network centrality parameters and allows the user to analyze existing relationships between experimental data provided by the users and node centrality values computed by the plug-in. CentiScaPe allows identifying network nodes that are relevant from both experimental and topological viewpoints. CentiScaPe also provides a Boolean logic-based tool that allows easy characterization of nodes whose topological relevance depends on more than one centrality. Finally, different graphic outputs and the included description of biological significance for each computed centrality facilitate the analysis by the end users not expert in graph theory, thus allowing easy node categorization and experimental prioritization.
Provides an interface to visualize data through network modelling techniques. Qgraph is an R package that accommodates capacities for spotting patterns by visualizing data in a novel way: through networks. This method enables the researcher to represent complex statistical patterns in clear pictures, without the need for data reduction methods. qgraph is designed to be usable by researchers new to R, while at the same time offering more advanced customization options for experienced R users.
Uses as a software for the visual creation, transformation, exploration, analysis, and representation of network data. Visone is a long-term research project, in which models and algorithms to integrate and advance the analysis and visualization of social networks are being developed. It is specifically designed to allow experts and novices alike to apply innovative and advanced visual methods with ease and accuracy.