NDLI: Statistically optimal modular partitioning of directed graphs

Content Provider	IEEE Xplore Digital Library
Author	Yu-Teng Chang Pantazis, D. Leahy, R.M.
Copyright Year	2010
Description	Author affiliation: Signal & Image Processing Inst., University of Southern California, Los Angeles, 90089-2564, USA (Yu-Teng Chang; Pantazis, D.; Leahy, R.M.)
Abstract	Network models can be used to represent interacting subsystems in the brain or other biological systems. These subsystems can be identified by partitioning a graph representation of the network into highly connected modules. In this paper we describe a modularity-based partitioning method based on a Gaussian model of a directed graph. Using the degrees of each node, we first compute the conditional expected value of the connection weights. The resulting adjacency matrix forms a null model for the network which does not favor any particular partition. By comparing this null model to the true adjacency graph, we can perform a statistically optimal partitioning that maximizes modularity. Similarly to other modularity-based partitioning methods, the solution is found using spectral matrix decomposition. The process can be iterated to find multiple subgraphs. We demonstrate this approach through simulations and application to standard biological and other network data.
Starting Page	1075
Ending Page	1079
File Size	948268
Page Count	5
File Format	PDF
ISBN	9781424497225
ISSN	10586393
e-ISBN	9781424497218
DOI	10.1109/ACSSC.2010.5757568
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Communities Biological system modeling Mathematical model Network topology Computational modeling Topology Optimization Conditional Expected Gaussian Random Network Modularity Graph Partitioning Directed Graph
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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