Co-clustering documents and words using bipartite spectral graph partitioning
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Clustering Using a Similarity Measure Based on Shared Near Neighbors
IEEE Transactions on Computers
A matrix-based multilevel approach to identify functional protein modules
International Journal of Bioinformatics Research and Applications
Multilevel approaches for large-scale proteomic networks
International Journal of Computer Mathematics - Bioinformatics
VECPAR'06 Proceedings of the 7th international conference on High performance computing for computational science
Triangular clique based multilevel approaches to identify protein functional modules
VECPAR'06 Proceedings of the 7th international conference on High performance computing for computational science
Discovering overlapping modules and bridge proteins in proteomic networks
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
Crosstalk measures for analyzing biological networks in breast cancer
Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
A multilevel approach to identify functional modules in a yeast protein-protein interaction network
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
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We describe an approach to clustering the yeast protein-protein interaction network in order to identify functional modules, groups of proteins forming multi-protein complexes accomplishing various functions in the cell. We have developed a clustering method that accounts for the small-world nature of the network. The algorithm makes use of the concept of k-cores in a graph, and employs recursive spectral clustering to compute the functional modules. The computed clusters are annotated using their protein memberships into known multi-protein complexes in the yeast. We also dissect the protein interaction network into a global subnetwork of hub proteins (connected to several clusters), and a local network consisting of cluster proteins.