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Provides versatile and interactive structure analysis tools for residue interaction networks (RINs) and enables dynamic 2D and 3D views. RINalyzer is a software tool for the automatized generation, 2D visualization, and interactive analysis of residue interaction networks. RINalyzer is available as a plugin for Cytoscape, an established open-source software platform for the analysis and visualization of biological networks. In particular, RINalyzer complements current 3D structural viewers and modelling tools and enables the interactive, visual analysis of protein structures with RINs.
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.
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.
CentiScaPe / Centralities for Cytoscape
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.
A tool for determination of hierarchical layers of overlapping network modules and community centrality. The ModuLand Cytoscape plug-in provides a user-friendly and efficient method to identify and visualize a hierarchy of extensively overlapping modules, and determines key network positions (like module cores and bridges). As shown by several case studies, modules identified by the plug-in correspond to biologically meaningful groups, module cores help the identification of biological functions and inter-modular nodes have a key role in a variety of biological networks.
A Java-library and user-friendly plug-in for the computation and investigation of weighted and unweighted centralities in biological networks. CentiLib provides 17 different node centrality and four graph centrality measures in a user-friendly interface and supports the exploration of analysis results within the networks. With the ability to quantitatively analyze biological networks in an interactive and visual manner, CentiLib supports a better understanding of complex biological networks and processes. The GUI is available as a plugin for Vanted and Cytoscape.
Combines residue interaction network (RIN) centrality analyses with direct visualization of the predicted local flexibility of the associated sequence. RINspector is a Cytoscape app that links the three aspects of structure, network and flexibility, making it a useful for the investigation of protein structure and subsequent applications, such as protein design or the selection of mutants for mutagenesis experiments. It performs one or several centrality analyses: (a) residue centrality, based on the change of average shortest path length under removal of each node; (b) betweenness centrality; (c) closeness centrality.
Connects Cytoscape on the desktop to a server environment using a Neo4j database. cyNeo4j is a Cytoscape module developed to increase the performance of network analysis algorithms. It permits researchers to use the Cypher query language to navigate and explore networks too large for typical desktop computers. This method also allows for an iterative execution of an algorithm by sending multiple requests to the server enabling the user to interrupt the execution or observe intermediate results.
SANTA / Spatial Analysis of Network Associations
A package which provides methods for measuring the strength of association between a network and a phenotype. SANTA quantifies the strength of association between a gene set and a network, and functionally annotates molecular networks like other enrichment methods annotate lists of genes. SANTA can (i) functionally annotate experimentally derived networks using a collection of curated gene sets and (ii) annotate experimentally derived gene sets using a collection of curated networks, as well as (iii) prioritize genes for follow-up analyses.
A comprehensive online resource that provides over 110 definitions of different centrality indices, their computational methods, and algorithms in the form of an encyclopedia. Centiserve is also an R package for the statistical R software, which contain 34 functions for calculating centrality indices. This encyclopedia of centrality with its computational facilities was created to help researchers to make better choices of measures by reviewing the previous works, come up with new ideas, and avoid repetition. The second goal was to develop an application, which calculates more centrality measures in comparison to other tools. Access to all measures will not only help scientists to develop and optimize indices, but also provide an opportunity to calculate more centrality values for meaningful analysis of biological networks.
CentiBiN / Centralities in Biological Networks
A tool for the computation and exploration of centralities in biological networks such as protein-protein interaction networks. CentiBiN computes 17 different centralities for directed or undirected networks, ranging from local measures, that is, measures that only consider the direct neighbourhood of a network element, to global measures. CentiBiN supports the exploration of the centrality distribution by visualizing central elements within the network and provides several layout mechanisms for the automatic generation of graphical representations of a network.
A Java plugin for Cytoscape, a facilitated platform for the analysis and visualization of molecular interaction networks based on web application, Hubba. cytoHubba provides a user-friendly interface to analyze topology of protein-protein interaction networks, such as human, yeast, fly etc. CytoHubba provides 11 topological analysis methods including Degree, Edge Percolated Component, Maximum Neighborhood Component, Density of Maximum Neighborhood Component, Maximal Clique Centrality and six centralities (Bottleneck, EcCentricity, Closeness, Radiality, Betweenness, and Stress) based on shortest paths. These essential nodes may serve as candidates of drug-targets for developing novel therapy of human diseases, such as cancer or infectious disease caused by emerging pathogens.
A convenient app for network centrality analysis. CytoNCA supports eight typical centralities: Betweeness Centrality [1], Closeness Centrality [2], Degree Centrality [3], Eigenvector Centrality [4], Local Average Connectivity-based method [5], Network Centrality [6], Subgraph Centrality [7], Information Centrality [8] for both weighted as well as unweighted networks. The biological characters from other sources could also be analyzed and assessed by CytoNCA. This makes CytoNCA an excellent tool for calculating centrality, evaluating and visualizing biological networks.
FUGA / Functional Genomics Assistant
A MATLAB toolbox for inference and analysis of biological and cellular networks, biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology.
SBEToolbox / Systems Biology and Evolution Toolbox
An open-source Matlab toolbox for biological network analysis. SBEToolbox takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven Graphical User Interface (GUI) of SBEToolbox enables easy access to various network and graph algorithms for programmers and non-programmers alike.
GTNA / Graph-Theoretic Network Analyzer
Uses as a graph-theoretic network analysis. GTNA is an efficient Java-based toolkit for the comprehensive analysis of complex network graphs. It is simple to extend through a well defined plugin interface for metrics, network descriptions and network generator models. GTNA is an approach that combines simulating technological networks with an indepth structural analysis into one toolkit. GTNA additionally implements all major metrics used for the analysis of complex graphs in sociology, biology, and computer science.
Provides a method for predicting essential proteins. TEO is an algorithm that combines protein-protein interaction (PPI) data, gene-expression profiles and gene ontology (GO) annotation data. It permits users to: (i) characterize co-module by using the edge clustering coefficient of the network’s topological structure; (ii) evaluate co-expression patterns by calculating the Pearson correlation coefficient between two considered gene-expression profiles; and (iii) measure functional similarity of two interacting proteins by calculating the GO similarity based on GO annotation terms.
JUNG / Java Universal Network/Graph
Provides a common and extendible language for the modelling, analysis, and visualization of data that can be represented as a graph or network. JUNG is designed to support a variety of representations of entities and their relations, such as directed and undirected graphs, multi-modal graphs, graphs with parallel edges, and hypergraphs. It provides a mechanism for annotating graphs, entities, and relations with metadata. This facilitates the creation of analytic tools for complex data sets that can examine the relations between entities as well as the metadata attached to each entity and relation.
NetVis Module
Analyzes and visualizes social networks using data from csv files, online surveys, and dispersed teams. The NetVis Module is a free open source web-based tool that gives opportunities to explore social networks through an online application that integrates data analysis and visualization. It simulates temporary social network data through specifying parameters and subgroup configuration through specifying parameters. It also permits to create or upload a social network through typing or copying/pasting data.
Implements recent advances in the statistical modelling of networks. Sna provides a comprehensive framework for ergm-based network modelling, including tools for model estimation, model evaluation, model-based network simulation, and network visualization. This broad functionality is powered by a central Markov chain Monte Carlo (MCMC) algorithm. It includes cross-sectional and temporal/dynamic modelling, latent space and latent cluster models, and models for valued/ranked/signed ties.
Allows to build Semantic Web applications. AllegroGraph is a database and an application framework which enables the extraction of sophisticated decision insights and predictive analytics from their highly complex, distributed data that can’t be answered with conventional databases. The software employs a combination of semantic and graph technologies that process data with contextual and conceptual intelligence. It aims to support predictive analytics that help companies make real-time decisions.
NodeXL / Network Overview Discovery and Exploration for Excel
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.
JGraphT-sna / Social Network Analysis addon
Implements several algorithms used in social network analysis (SNA) on top of the JGraphT library. JGraphT-sna is a Java library for Graphs. It supports generics, where nodes and edges can be of user-defined types. The intention is to support as many SNA-specific algorithms as possible. This algorithm focuses on centrality measures (degree centrality, closeness centrality, betweenness centrality, eigenvector centrality, etc.), hierarchy detection algorithms, random-error generators and generators for complex network types and many others.
SocNetV / Social Network Visualizer
Offers resources to draw social networks with a few clicks on a virtual canvas, load field data from a file in a supported format or crawl the internet to create a social network of connected webpages. SocNetV is a cross-platform, user-friendly free software application for social network analysis and visualization. It also permits to Edit actors and ties through point-and-click, analyse graph and social network properties, produce beautiful HTML reports and embed visualization layouts to the network.
A Cytoscape plug-in for virtual knock-out experiments on complex networks. Interference is a Centralities based measure. Interference plug-in computes the Interference values for the following centralities: Eccentricity, Closeness, Betweenness, Stress, Centroid, Radiality. The Interference plug-in allows you identifying the area of influence of single nodes or group of nodes. Specifically, Interference 1) computes the centralities value of the network 2) remove the node(s) of interest 3) recompute the centralities in the new network (the one where the node(s) have been removed) 4) evaluate the differences between the centralities in the two networks.
Helps researchers and developers in their daily tasks of dynamic problem modelling and of classical graph management tasks: creation, processing, display, etc. GraphStream is a Java-based library that may be used for teaching purpose. Its purpose is to create and manipulate dynamic graphs in order to study them and to use them in simulations. GraphStream is built upon an event-based engine and its whole conception is object oriented, so each element of the graph (nodes and edges) but also each attribute that qualify these elements are objects.
Sentinel Visualizer
Gives a powerful and configurable knowledgebase that makes it easy to store any information: text, graphics, documents, video, audio, etc. Sentinel Visualizer is a data visualization and analysis solution for researcher’s big data. Its database driven data visualization platform lets quickly see multi-level links among entities and model different relationship types. Advanced drawing and redrawing features generate optimized views to highlight the most important entities.
CINNA / Central Informative Nodes in Network Analysis
Calculates, compares, assorts, and visualizes network centrality measures together. CINNA is an R package that provides a collection of functions. This package provides different visualization techniques for comparing results of centrality analysis and dimension-al reduction methods including heatmap, dendrogram and pair-wise scatter plot. It includes about 23 user-level functions along with 5 natural network examples which helps the user to have a different experience from the centrality network analysis.
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