Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/40912
Title: NeMoFinder: Dissecting genome-wide protein-protein interactions with meso-scale network motifs
Authors: Chen, J.
Hsu, W. 
Lee, M.L. 
Ng, S.-K.
Keywords: Graph mining
Network motif
Protein-protein interaction network
Issue Date: 2006
Source: Chen, J.,Hsu, W.,Lee, M.L.,Ng, S.-K. (2006). NeMoFinder: Dissecting genome-wide protein-protein interactions with meso-scale network motifs. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2006 : 106-115. ScholarBank@NUS Repository.
Abstract: Recent works in network analysis have revealed the existence of network motifs in biological networks such as the protein-protein interaction (PPI) networks. However, existing motif mining algorithms are not sufficiently scalable to find mesoscale network motifs. Also, there has been little or no work to systematically exploit the extracted network motifs for dissecting the vast interactomes. We describe an efficient network motif discovery algorithm, NeMoFinder, that can mine meso-scale network motifs that are repeated and unique in large PPI networks. Using NeMoFinder, we successfully discovered, for the first time, up to size-12 network motifs in a large whole-genome S. cerevisiae (Yeast) PPI network. We also show that such network motifs can be systematically exploited for indexing the reliability of PPI data that were generated via highly erroneous high-throughput experimental methods. Copyright 2006 ACM.
Source Title: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
URI: http://scholarbank.nus.edu.sg/handle/10635/40912
ISBN: 1595933395
Appears in Collections:Staff Publications

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