Experimental study of minimum cut algorithms
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
Future Generation Computer Systems
A clustering algorithm based on graph connectivity
Information Processing Letters
A Topological Measurement for Weighted Protein Interaction Network
CSB '05 Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference
Protein complex prediction via cost-based clustering
Bioinformatics
Iterative Cluster Analysis of Protein Interaction Data
Bioinformatics
Rearrangement Clustering: Pitfalls, Remedies, and Applications
The Journal of Machine Learning Research
Protein Interaction Networks: Computational Analysis
Protein Interaction Networks: Computational Analysis
ANN Based Protein Function Prediction Using Integrated Protein-Protein Interaction Data
IJCBS '09 Proceedings of the 2009 International Joint Conference on Bioinformatics, Systems Biology and Intelligent Computing
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Protein-protein interactions (PPIs) play fundamental roles in nearly all biological processes and differ based on the composition, affinity and lifetime of the association. A vast amount of PPI data for various organisms is available from MIPS, DIP and other sources. The identification of functional modules in PPI network is of great interest because they often reveal unknown functional ties between proteins and hence predict functions for unknown proteins. However the noise in the PPI network and the complexity of the network structure present great challenges to the functional module detection problem. In this paper, we propose a flexible framework which integrates the topological features of the network and the Ant Colony Optimization (ACO) algorithm to solve the problem. We first create an reliability measurement of the protein-protein interaction to rebuild the PPI network. Then we reformulate the problem to an optimal path detecting problem from the perspective of information flow. Last, an ACO-based functional module detection method is proposed by simulating the ants' behavior. We evaluate the proposed technique on the yeast protein-protein interaction network with MIPS functional categories and compare it with several other existing techniques. Our experiments show that our approach achieves better accuracy than other existing methods.