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Information-theoretic approach to network modularity

Infomod is software for identifying clusters or communities in a network, based on the Information Bottleneck, using a greedy agglomerative algorithm as described in "Information-theoretic approach to network modularity". This software also outputs a measure of how modular (see paper) the network is. The software also implements an improved (more useful) technique for calculating the Jensen-Shannon divergence between probability distributions, based on its series expansion as described in "A non-negative expansion for small Jensen-Shannon Divergences". Infomod is implemented in MATLAB and can be downloaded at the sourceforge page.

This software is free for scientific use. Please contact us if you plan to use this software for commercial purposes. Do not further distribute without prior permission of the authors. If used in your scientific work, please cite as:

Etay Ziv, Manuel Middendorf and Chris H. Wiggins, "Information-theoretic approach to network modularity", Phys. Rev. E 71, 046117 (2005) (paper, bibtex citation)

along with the paper that describes a novel numerical implementation of the JS entropy calculation

Anil Raj and Chris H. Wiggins (2008), "A non-negative series expansion for small Jensen-Shannon Divergences", arXiv:0810.5117[stat.ML] (paper, bibtex citation)

Please forward links to related and resulting publications so we can learn about your research.

A screenshot of infomod:

Information Curve

This work was funded by the National Institutes of Health under grants #PN2 EY016586-03 and #1U54CA121852-01A1 and the National Science Foundation under grants #ECS-0332479 and #ECS-0425850.


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