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Updated version of the NOESIS Network Analyzer

posted Aug 7, 2017, 11:32 AM by Fernando Berzal

An updated version of our user-friendly tool for the analysis and visualization of networks, freely available for download at http://noesis.ikor.org/download.



NOESIS Network Analyzer main features

  • Supported network file formats (for analyzing your own networks):

    • GML

    • GraphML

    • GDF

  • Adjustable network visualization:

    • Drag & drop graphical user interface.

    • Automatic layout methods (Fruchterman-Reingold, Kamada-Kawai, hierarchical, radial, random, and regular layouts).

    • Multiple visualization options (styles, colors & sizes).
       
    • Export network images in SVG, PNG, or JPEG format.

  • Network models:

    • Random networks: Erdös-Renyi, Gilbert, Watts-Strogatz, Barabasi-Albert, and Price models.

    • Regular networks: Star, ring, tandem, mesh, toroidal, hypercube, and binary tree networks.

  • Network analysis techniques: 

    • Network structural properties (degree, degree assortativity, eccentricity, average path length, closeness, decay, betweenness, PageRank, HITS, eigenvector centrality, Katz centrality, clustering coefficient, connected components, link betweenness, link embeddedness, link neighborhood overlap...).

    • Community detection methods (Kernighan-Lin partitioning; Newman-Girvan & Radicchi hierarchical community detection; single-link, average-link & complete link hierarchical clustering; fast & multi-step greedy modularity-based community detection; EIG1, KNSC1 & UKMeans spectral community detection, and BigCLAM overlapping community detection).

    • Link scoring & prediction methods (common neighbors, Adamic-Adar score, resource allocation, Jaccard score, preferential attachment, Salton score, Sorensen score, hub-promoted & hub-depressed scores, local & global Leicht-Holme-Newman score, Katz score, random walks & random walks with restarts, flow propagation, pseudoinverse Laplacian score, average commute time score & random forest kernel score).

System requirements: Java Runtime Environment version 8 (JRE8). 

NOTE: The efficient implementation of network analysis techniques makes use of multiple cores in multicore processors when available.



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