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» On Generating Random Network Structures: Connected Graphs
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117
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ICML
2005
IEEE
16 years 1 months ago
Predicting protein folds with structural repeats using a chain graph model
Protein fold recognition is a key step towards inferring the tertiary structures from amino-acid sequences. Complex folds such as those consisting of interacting structural repeat...
Yan Liu, Eric P. Xing, Jaime G. Carbonell
88
Voted
CONNECTION
2006
101views more  CONNECTION 2006»
15 years 14 days ago
High capacity, small world associative memory models
Models of associative memory usually have full connectivity or if diluted, random symmetric connectivity. In contrast, biological neural systems have predominantly local, non-symm...
Neil Davey, Lee Calcraft, Rod Adams
FOCS
2008
IEEE
15 years 6 months ago
Dynamic Connectivity: Connecting to Networks and Geometry
Dynamic connectivity is a well-studied problem, but so far the most compelling progress has been confined to the edge-update model: maintain an understanding of connectivity in a...
Timothy M. Chan, Mihai Patrascu, Liam Roditty
DCOSS
2009
Springer
15 years 5 months ago
Distributed Generation of a Family of Connected Dominating Sets in Wireless Sensor Networks
We study the problem of computing a family of connected dominating sets in wireless sensor networks (WSN) in a distributed manner. A WSN is modelled as a unit disk graph G = (V, E)...
Kamrul Islam, Selim G. Akl, Henk Meijer
BMCBI
2005
120views more  BMCBI 2005»
15 years 9 days ago
SpectralNET - an application for spectral graph analysis and visualization
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
Joshua J. Forman, Paul A. Clemons, Stuart L. Schre...