http://franz.com/agraph/allegrograph/
AllegroGraph® is a modern, high-performance, persistent graph database. AllegroGraph uses efficient memory utilization in combination with disk-based storage, enabling it to scale to billions of quads while maintaining superior performance. AllegroGraph supports SPARQL, RDFS++, and Prolog reasoning from numerous client applications.
http://www.brain-connectivity-toolbox.net/
The BCT contains a large selection of complex network measures in Matlab. These measures are increasingly used to characterize structural and functional brain connectivity datasets.
Bargaining centrality
Centroid value
Closeness centrality
Closeness Vitality
Current-Flow Betweenness centrality
Current-Flow Closeness centrality
Degree centrality
Eccentricity centrality
Eigenvector centrality
HITS
Hubbell Index
Katz Status Index
PageRank
Radiality centrality
Shortest-Paths Betweenness centrality
Stress centrality
Java standalone
Free
CentiLib
http://centilib.ipk-gatersleben.de/
CentiLib is a Java-library for the computation and investigation of weighted and unweighted centralities in biological networks.
Betweenness centrality
Centroid centrality
Closeness centrality
Current-flow closeness centrality
Current-flow betweenness centrality
Degree centrality
Eccentricity centrality
Eigenvector centrality
HITS
Hubbel index
Katz status index centrality
PageRank
Radiality centrality
Stress centrality
https://cran.r-project.org/web/packages/CINNA/
It is an R package available on CRAN repository specialized for network centrality analysis. It is a tool for centrality comparison using dimensional reduction algorithms
Dangalchev closeness centrality
Group centrality
Local bridging centrality
Harmonic centrality
Wiener index centrality
R Package
Free
cyto-Hubba
http://hub.iis.sinica.edu.tw/cytohubba/
cytoHubba is a Java plugin for Cytoscape, a facilitated platform for the analysis and visualization of molecular interaction networks based on web application, Hubba.
Bottleneck (BN)
Degree
Density of Maximum Neighborhood Component (DMNC)
Double Screening Scheme (DSS) of MNC || DMNC
Edge Percolated Component (EPC)
Maximum Neighborhood Component (MNC)
Cytoscape plugin
Free
CytoNCA
http://apps.cytoscape.org/apps/cytonca
Providing calculation, evaluation and visualization analysis for several centralities of weighted and unweighted network.
Betweenness centrality
Closeness centrality
Degree centrality
Eigenvector centrality
Information centrality
Local Average Connectivity-based method (LAC)
Network centrality (NC)
Subgraph centrality
Cytoscape Plugin
Free
EgoNet
http://escoladeredes.net/profiles/blogs/egonet-1 http://sourceforge.net/projects/egonet/
EgoNet (Egocentric Network Study Software) for the collection and analysis of egocentric social network data.[1] It helps the user to collect and analyse all the egocentric network data (all social network data of a website on the Internet), and provide general global network measures and data matrixes that can be used for further analysis by other software.
http://graphstream-project.org/
GraphStream is a Java library for the modeling and analysis of dynamic graphs. You can generate, import, export, measure, layout and visualize them.
http://graph-tool.skewed.de/
Graph-tool is an efficient Python module for manipulation and statistical analysis of graphs (a.k.a. networks). The core data structures and algorithms are implemented in C++.
http://jung.sourceforge.net/
The Java Universal Network/Graph Framework--is a software library that provides a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network.
Average distance
Betweenness centrality
Barycenter centrality
Closeness centrality
Degree centrality
Eccentricity centrality
Eigenvector centrality
HITS
HITS with priors
Markov centrality
PageRank
PageRank with priors
Random walk betweenness
http://www.sfu.ca/personal/archives/richards/Multinet/Pages/multinet.htm
MultiNet is a data analysis package that can be used for ordinary data (in which you have a file that has one line of data for each case) and for network data (in which there are two files -- the "node" file describes the individuals and the "link" file describes the connections between individuals).
Betweenness centrality
Closeness centrality
Eccentricity centrality
Eigenvector centrality
Eigenvector centrality arnoldi
Eigenvector centrality power
Shortest path based centrality
Stress centrality
Windows
Commercial
NetMiner
http://www.netminer.com/
NetMiner is an premium software tool for Exploratory Analysis and Visualization of Network Data.
Windows
Commercial
NetVis Module
http://www.netvis.org/
The NetVis Module is a free open source web-based tool to analyze and visualize social networks using data from csv files, online surveys, and dispersed teams.
https://networkit.iti.kit.edu/
NetworKit is a growing open-source toolkit for high-performance network analysis. Its aim is to provide tools for the analysis of large networks in the size range from thousands to billions of edges.
ApproxBetweenness centrality
Betweenness centrality
Closeness centrality
Degree centrality
Dynamic approximation of Betweenness centrality
Eigenvector centrality
Katz centrality, k-path centrality
Local clustering coefficients
PageRank
Spanning edge centrality
Spectral centrality
Top-k Closeness (faster algorithm for computing only the top-k nodes with highest closeness)
Betweenness centrality
Burt’s measure of constraint (structural holes)
Closeness centrality
Clustering coefficient
Degree distributions
Hubs-Authorities
Summing up Values of Line
http://rinalyzer.de/
RINalyzer provides a number of important methods for analyzing and visualizing residue interaction networks (RINs).
Current flow betweenness centrality
Current flow closeness centrality
Random walk betweenness centrality
Random walk closeness centrality
Shortest path betweenness centrality
Shortest path closeness centrality
Weighted degree centrality
http://bioconductor.org/packages/release/bioc/html/SANTA.html
Spatial Analysis of Network Associations.
This package provides methods for measuring the strength of association between a network and a phenotype. It does this by measuring clustering of the phenotype across the network. Vertices can also be individually ranked by their strength of association with high-weight vertices.
http://socnetv.sourceforge.net/
Social Networks Visualizer (SocNetV) is a cross-platform, user-friendly tool for the analysis and visualization of Social Networks.
Betweenness centrality
Closeness centrality
Degree centrality
Degree Prestige (inDegree)
Eccentricity centrality
Influence Range Closeness centrality
Information centrality
PageRank Prestige
Power centrality
Proximity Prestige
Stress centrality
Betweenness centrality
Bonacich power centrality
Closeness centrality
Degree centrality
Distance weighted fragmentation
Eigenvector centrality
Flow betweenness centrality
Fragmentation centrality
Hubs and authorities centrality
K-step reach centrality
Information centrality
Political independence index (pii)
Proximal betweenness centrality
Reverse closeness centrality
Windows
Commercial
Visone
http://visone.info/
Visone is a long-term research project (team), in which models and algorithms to integrate and advance the analysis and visualization of social networks are being developed.
KONGANTI, K., WANG, G., YANG, E., CAI, J. J., KONGANTI, K., WANG, G., YANG, E. & CAI, J. J. 2013. SBEToolbox: A Matlab Toolbox for Biological Network Analysis. Evolutionary Bioinformatics, 9, 355-362.
DOI: 10.4137/EBO.S12012
DROZDOV, I., OUZOUNIS, C. A., SHAH, A. M. & TSOKA, S. 2011. Functional Genomics Assistant (FUGA): a toolbox for the analysis of complex biological networks. BMC research notes, 4, 462.
DOI: 10.1186/1756-0500-4-462
JUNKER, B. H., KOSCHÜTZKI, D. & SCHREIBER, F. 2006. Exploration of biological network centralities with CentiBiN. BMC bioinformatics, 7, 219.
DOI: 10.1186/1471-2105-7-219
RUBINOV, M. & SPORNS, O. 2010. Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52, 1059-1069.
DOI: 10.1016/j.neuroimage.2009.10.003
CSARDI, G. & NEPUSZ, T. 2006. The igraph software package for complex network research. InterJournal, Complex Systems, 1695. [http://igraph.org]
CARTER T. BUTTS (2014). sna: Tools for Social Network Analysis. R package version 2.3-2. http://CRAN.R-project.org/package=sna
A HAGBERG, D. S., P SWART. Exploring Network Structure, Dynamics, and Function using NetworkX. In: G VAROQUAUX, T. V., J MILLMAN, ed. Proceedings of the 7th Python in Science conference (SciPy 2008), 2008. 11-15.
BASTIAN, M., HEYMANN, S. & JACOMY, M. 2009. Gephi: An Open Source Software for Exploring and Manipulating Networks.
DONCHEVA, N. T., KLEIN, K., DOMINGUES, F. S. & ALBRECHT, M. 2011. Analyzing and visualizing residue networks of protein structures. Trends in Biochemical Sciences, 36, 179-182.
DOI: 10.1016/j.tibs.2011.01.002
BORGATTI, S. P., EVERETT, M. G. & FREEMAN, L. C. 2002. Ucinet for Windows: Software for social network analysis. Harvard, MA: Analytic Technologies.
BOLDI, P. & VIGNA, S. 2004. The webgraph framework I: compression techniques. Proceedings of the 13th international conference on World Wide Web. New York, NY, USA: ACM.
DOI: 10.1145/988672.988752
Yu Tang, Min Li, Jianxin Wang, CytoNCA: a cytoscape plugin for centrality analysis and evaluation of biological network
SCHILLER, B., BRADLER, D., SCHWEIZER, I., M, M., #252, HLH, #228, USER & STRUFE, T. 2010. GTNA: a framework for the graph-theoretic network analysis. Proceedings of the 2010 Spring Simulation Multiconference. Orlando, Florida: Society for Computer Simulation International.
DOI: 10.1145/1878537.1878653
ASSENOV, Y., RAMÍREZ, F., SCHELHORN, S.-E., LENGAUER, T. & ALBRECHT, M. 2008. Computing topological parameters of biological networks. Bioinformatics, 24, 282-284.
LANGFELDER, P. & HORVATH, S. 2008. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics, 9, 559.
PMID: 19114008DOI: 10.1186/1471-2105-9-559
V. Batagelj, A. Mrvar: Pajek – Program for Large Network Analysis. Home page: http://vlado.fmf.uni-lj.si/pub/networks/pajek/
Smith, M., Milic-Frayling, N., Shneiderman, B., Mendes Rodrigues, E., Leskovec, J., Dunne, C., (2010). NodeXL: a free and open network overview, discovery and exploration add-in for Excel 2007/2010, http://nodexl.codeplex.com/ from the Social Media Research Foundation, http://www.smrfoundation.org
CHEN, S.-H., CHIN, C.-H., WU, H.-H., HO, C.-W., KO, M.-T. & LIN, C.-Y. cyto-Hubba: A Cytoscape plug-in for hub object analysis in network biology. 20th International Conference on Genome Informatics, 2009.
SCARDONI, G., PETTERLINI, M. & LAUDANNA, C. 2009. Analyzing biological network parameters with CentiScaPe. Bioinformatics, 25, 2857-2859.
DOI: 10.1093/bioinformatics/btp517
GRÄßLER, J., KOSCHÜTZKI, D. & SCHREIBER, F. 2012. CentiLib: comprehensive analysis and exploration of network centralities. Bioinformatics, 28, 1178-1179.
DOI: 10.1093/bioinformatics/bts106
BRANDES, U. W. D.(2003).“Visone. Analysis and Visualization of Social Networks”. Special Issue on Graph Drawing Software, Springer-Verlag, Springer Series in Mathematics and Visualization, Springer-Verlag, págs, 321-340.
Cornish A and Markowetz F (2014). SANTA: Spatial Analysis of Network Associations. R package version 1.4.0.
SZALAY-BEKŐ, M., PALOTAI, R., SZAPPANOS, B., KOVÁCS, I. A., PAPP, B. & CSERMELY, P. 2012. ModuLand plug-in for Cytoscape: determination of hierarchical layers of overlapping network modules and community centrality. Bioinformatics, 28, 2202-2204.