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» Methods for Random Modularization of Biological Networks
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WEA
2010
Springer
316views Algorithms» more  WEA 2010»
13 years 11 months ago
Modularity-Driven Clustering of Dynamic Graphs
Maximizing the quality index modularity has become one of the primary methods for identifying the clustering structure within a graph. As contemporary networks are not static but e...
Robert Görke, Pascal Maillard, Christian Stau...
ICDM
2009
IEEE
125views Data Mining» more  ICDM 2009»
14 years 19 days ago
A Fully Automated Method for Discovering Community Structures in High Dimensional Data
—Identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. Recently s...
Jianhua Ruan
JSAC
2010
138views more  JSAC 2010»
13 years 4 months ago
Dynamic conjectures in random access networks using bio-inspired learning
—Inspired by the biological entities’ ability to achieve reciprocity in the course of evolution, this paper considers a conjecture-based distributed learning approach that enab...
Yi Su, Mihaela van der Schaar
BMCBI
2011
12 years 9 months ago
MINE: Module Identification in NEtworks
Background: Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of function...
Kahn Rhrissorrakrai, Kristin C. Gunsalus
BICOB
2009
Springer
14 years 17 days ago
Graph Spectral Approach for Identifying Protein Domains
Here we present a simple method based on graph spectral properties to automatically partition multi-domain proteins into individual domains. The identification of structural domain...
Hari Krishna Yalamanchili, Nita Parekh