Data structures for weighted matching and nearest common ancestors with linking
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
Quality matching and local improvement for multilevel graph-partitioning
Parallel Computing - Special issue on graph partioning and parallel computing
A linear-time heuristic for improving network partitions
DAC '82 Proceedings of the 19th Design Automation Conference
A fast kernel-based multilevel algorithm for graph clustering
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
The architecture of a proteomic network in the yeast
CompLife'05 Proceedings of the First international conference on Computational Life Sciences
A multi-level approach for document clustering
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part I
Multilevel approaches for large-scale proteomic networks
International Journal of Computer Mathematics - Bioinformatics
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
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Identifying functional modules is believed to reveal most cellular processes. There have been many computational approaches to investigate the underlying biological structures [9, 4, 10, 6]. A spectral clustering method plays a critical role identifying functional modules in a yeast protein-protein network in [6, 4]. We present an unweighted-graph version of a multilevel spectral algorithm which more accurately identifies protein complexes with less computational time.