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Volumn 5, Issue 9, 2010, Pages 1-10

Diffusion model based spectral clustering for protein- protein interaction networks

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ADJUSTABLE DIFFUSION MATRIX BASED SPECTRAL CLUSTERING; ARTICLE; CAENORHABDITIS ELEGANS; CONTROLLED STUDY; DECOMPOSITION; DIFFUSION; ESCHERICHIA COLI; FEASIBILITY STUDY; INTERMETHOD COMPARISON; LEARNING ALGORITHM; MOLECULAR DYNAMICS; PROCESS DEVELOPMENT; PROTEIN ANALYSIS; PROTEIN POLYMORPHISM; PROTEIN PROTEIN INTERACTION; REPRODUCIBILITY; SPECTROSCOPY; STATISTICAL ANALYSIS; STATISTICAL MODEL; YEAST; ALGORITHM; BIOLOGICAL MODEL; CHEMISTRY; EVALUATION; METABOLISM; METHODOLOGY; PROTEIN BINDING; SACCHAROMYCES CEREVISIAE;

EID: 77958537453     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0012623     Document Type: Article
Times cited : (27)

References (41)
  • 1
    • 0742305866 scopus 로고    scopus 로고
    • Network biology: Understanding the cell's functional organization
    • Barabasi AL, Oltvai ZN (2004) Network biology: understanding the cell's functional organization. Nat Rev Genet 5: 101-113.
    • (2004) Nat Rev Genet , vol.5 , pp. 101-113
    • Barabasi, A.L.1    Oltvai, Z.N.2
  • 2
    • 13844264514 scopus 로고    scopus 로고
    • Iterative cluster analysis of protein interaction data
    • Arnau V, Mars S, Marin I (2005) Iterative cluster analysis of protein interaction data. Bioinformatics 21: 364-378.
    • (2005) Bioinformatics , vol.21 , pp. 364-378
    • Arnau, V.1    Mars, S.2    Marin, I.3
  • 3
    • 0037417817 scopus 로고    scopus 로고
    • Modular organization of cellular networks
    • Rives AW, Galitski T (2003) Modular organization of cellular networks. Proc Natl Acad Sci U S A 100: 1128-1133.
    • (2003) Proc Natl Acad Sci U S A , vol.100 , pp. 1128-1133
    • Rives, A.W.1    Galitski, T.2
  • 4
    • 33845955474 scopus 로고    scopus 로고
    • Inferring topology from clustering coefficients in protein-protein interaction networks
    • Friedel CC, Zimmer R (2006) Inferring topology from clustering coefficients in protein-protein interaction networks. BMC Bioinformatics 7: 519.
    • (2006) BMC Bioinformatics , vol.7 , pp. 519
    • Friedel, C.C.1    Zimmer, R.2
  • 5
    • 0346156102 scopus 로고    scopus 로고
    • Detection of functional modules from protein interaction networks
    • Pereira-Leal JB, Enright AJ, Ouzounis CA (2004) Detection of functional modules from protein interaction networks. Proteins 54: 49-57.
    • (2004) Proteins , vol.54 , pp. 49-57
    • Pereira-Leal, J.B.1    Enright, A.J.2    Ouzounis, C.A.3
  • 6
    • 25444490121 scopus 로고    scopus 로고
    • The use of edge-betweenness clustering to investigate biological function in protein interaction networks
    • Dunn R, Dudbridge F, Sanderson CM (2005) The use of edge-betweenness clustering to investigate biological function in protein interaction networks. BMC Bioinformatics 6: 39.
    • (2005) BMC Bioinformatics , vol.6 , pp. 39
    • Dunn, R.1    Dudbridge, F.2    Sanderson, C.M.3
  • 7
    • 33846681448 scopus 로고    scopus 로고
    • Modular organization of protein interaction networks
    • Luo F, Yang Y, Chen CF, Chang R, Zhou J, et al. (2007) Modular organization of protein interaction networks. Bioinformatics 23: 207-214.
    • (2007) Bioinformatics , vol.23 , pp. 207-214
    • Luo, F.1    Yang, Y.2    Chen, C.F.3    Chang, R.4    Zhou, J.5
  • 8
    • 42749100809 scopus 로고    scopus 로고
    • Fast algorithm for detecting community structure in networks
    • Newman ME (2004) Fast algorithm for detecting community structure in networks. Phys Rev E Stat Nonlin Soft Matter Phys 69: 066133.
    • (2004) Phys Rev E Stat Nonlin Soft Matter Phys , vol.69 , pp. 066133
    • Newman, M.E.1
  • 10
    • 34547852262 scopus 로고    scopus 로고
    • An ensemble framework for clustering protein-protein interaction networks
    • Asur S, Ucar D, Parthasarathy S (2007) An ensemble framework for clustering protein-protein interaction networks. Bioinformatics 23: i29-40.
    • (2007) Bioinformatics , vol.23
    • Asur, S.1    Ucar, D.2    Parthasarathy, S.3
  • 11
    • 2942552459 scopus 로고    scopus 로고
    • An automated method for finding molecular complexes in large protein interaction networks
    • Bader GD, Hogue CW (2003) An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4: 2.
    • (2003) BMC Bioinformatics , vol.4 , pp. 2
    • Bader, G.D.1    Hogue, C.W.2
  • 12
    • 10244264813 scopus 로고    scopus 로고
    • Protein complex prediction via cost-based clustering
    • King AD, Przulj N, Jurisica I (2004) Protein complex prediction via cost-based clustering. Bioinformatics 20: 3013-3020.
    • (2004) Bioinformatics , vol.20 , pp. 3013-3020
    • King, A.D.1    Przulj, N.2    Jurisica, I.3
  • 13
    • 0038074373 scopus 로고    scopus 로고
    • Topological structure analysis of the protein-protein interaction network in budding yeast
    • Bu D, Zhao Y, Cai L, Xue H, Zhu X, et al. (2003) Topological structure analysis of the protein-protein interaction network in budding yeast. Nucleic Acids Res 31: 2443-2450.
    • (2003) Nucleic Acids Res , vol.31 , pp. 2443-2450
    • Bu, D.1    Zhao, Y.2    Cai, L.3    Xue, H.4    Zhu, X.5
  • 14
    • 33748202182 scopus 로고    scopus 로고
    • Functional clustering of yeast proteins from the protein-protein interaction network
    • Sen TZ, Kloczkowski A, Jernigan RL (2006) Functional clustering of yeast proteins from the protein-protein interaction network. BMC Bioinformatics 7: 355.
    • (2006) BMC Bioinformatics , vol.7 , pp. 355
    • Sen, T.Z.1    Kloczkowski, A.2    Jernigan, R.L.3
  • 16
    • 0000521616 scopus 로고    scopus 로고
    • Superparamagnetic clustering of data
    • Blatt M, Wiseman S, Domany E (1996) Superparamagnetic clustering of data. Phys Rev Lett 76: 3251-3254.
    • (1996) Phys Rev Lett , vol.76 , pp. 3251-3254
    • Blatt, M.1    Wiseman, S.2    Domany, E.3
  • 17
  • 19
    • 34249851161 scopus 로고    scopus 로고
    • Clustering by common friends finds locally significant proteins mediating modules
    • Andreopoulos B, An A, Wang X, Faloutsos M, Schroeder M (2007) Clustering by common friends finds locally significant proteins mediating modules. Bioinformatics 23: 1124-1131.
    • (2007) Bioinformatics , vol.23 , pp. 1124-1131
    • Andreopoulos, B.1    An, A.2    Wang, X.3    Faloutsos, M.4    Schroeder, M.5
  • 21
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
    • Belkin M, Niyogi P (2003) Laplacian Eigenmaps for Dimensionality Reduction and Data Representation. Neural Computation 15: 1373-1396.
    • (2003) Neural Computation , vol.15 , pp. 1373-1396
    • Belkin, M.1    Niyogi, P.2
  • 23
    • 84898985184 scopus 로고    scopus 로고
    • Learning segmentation by random walks
    • Lee TK, Dietterich TG, Tresp V, eds., Cambridge: MIT Press
    • Meila M, Shi J (2001) Learning segmentation by random walks. In: Lee TK, Dietterich TG, Tresp V, eds. Advances in Nerual Information Processing Systems. Cambridge: MIT Press. pp 873-879.
    • (2001) Advances In Nerual Information Processing Systems , pp. 873-879
    • Meila, M.1    Shi, J.2
  • 25
    • 0142059836 scopus 로고    scopus 로고
    • Protein complexes and functional modules in molecular networks
    • Spirin V, Mirny LA (2003) Protein complexes and functional modules in molecular networks. Proc Natl Acad Sci U S A 100: 12123-12128.
    • (2003) Proc Natl Acad Sci U S A , vol.100 , pp. 12123-12128
    • Spirin, V.1    Mirny, L.A.2
  • 26
    • 33845357608 scopus 로고    scopus 로고
    • An algorithm for modularity analysis of directed and weighted biological networks based on edge-betweenness centrality
    • Yoon J, Blumer A, Lee K (2006) An algorithm for modularity analysis of directed and weighted biological networks based on edge-betweenness centrality. Bioinformatics 22: 3106-3108.
    • (2006) Bioinformatics , vol.22 , pp. 3106-3108
    • Yoon, J.1    Blumer, A.2    Lee, K.3
  • 28
    • 84887012398 scopus 로고    scopus 로고
    • Clustering using a random-walk based distance measure
    • Yen L, Vanvyve D, Wouters F, Fouss F, Verleysen M, et al. (2005) Clustering using a random-walk based distance measure. ESANN. pp 317-324.
    • (2005) ESANN , pp. 317-324
    • Yen, L.1    Vanvyve, D.2    Wouters, F.3    Fouss, F.4    Verleysen, M.5
  • 30
    • 27144450500 scopus 로고    scopus 로고
    • Diffusion processes on power-law small-world networks
    • Kozma B, Hastings MB, Korniss G (2005) Diffusion processes on power-law small-world networks. Phys Rev Lett 95: 018701.
    • (2005) Phys Rev Lett , vol.95 , pp. 018701
    • Kozma, B.1    Hastings, M.B.2    Korniss, G.3
  • 31
    • 35248856354 scopus 로고    scopus 로고
    • On spectral graph drawing
    • Koren Y (2003) On spectral graph drawing. Lect Notes Comput Sci 2697: 496-508.
    • (2003) Lect Notes Comput Sci , vol.2697 , pp. 496-508
    • Koren, Y.1
  • 32
    • 84900631115 scopus 로고    scopus 로고
    • Detecting network communities: A new systematic and efficient algorithm
    • Donetti L, Munoz M (2004) Detecting network communities: a new systematic and efficient algorithm. J Stat Mech: P10012.
    • (2004) J Stat Mech
    • Donetti, L.1    Munoz, M.2
  • 33
    • 33745012299 scopus 로고    scopus 로고
    • Modularity and community structure in networks
    • Newman ME (2006) Modularity and community structure in networks. Proc Natl Acad Sci U S A 103: 8577-8582.
    • (2006) Proc Natl Acad Sci U S A , vol.103 , pp. 8577-8582
    • Newman, M.E.1
  • 34
    • 12344269924 scopus 로고    scopus 로고
    • GO: TermFinder- open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes
    • Boyle EI, Weng S, Gollub J, Jin H, Botstein D, et al. (2004) GO:TermFinder- open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes. Bioinformatics 20: 3710-3715.
    • (2004) Bioinformatics , vol.20 , pp. 3710-3715
    • Boyle, E.I.1    Weng, S.2    Gollub, J.3    Jin, H.4    Botstein, D.5
  • 35
    • 75949120438 scopus 로고    scopus 로고
    • How and when should interactome-derived clusters be used to predict functional modules and protein function?
    • Song J, Singh M (2009) How and when should interactome-derived clusters be used to predict functional modules and protein function? Bioinformatics 25: 3143-3150.
    • (2009) Bioinformatics , vol.25 , pp. 3143-3150
    • Song, J.1    Singh, M.2
  • 36
    • 33751255087 scopus 로고    scopus 로고
    • Evaluation of clustering algorithms for proteinprotein interaction networks
    • Brohee S, van Helden J (2006) Evaluation of clustering algorithms for proteinprotein interaction networks. BMC Bioinformatics 7: 488.
    • (2006) BMC Bioinformatics , vol.7 , pp. 488
    • Brohee, S.1    van Helden, J.2
  • 38
    • 0242380634 scopus 로고    scopus 로고
    • CADLIVE for constructing a largescale biochemical network based on a simulation-directed notation and its application to yeast cell cycle
    • Kurata H, Matoba N, Shimizu N (2003) CADLIVE for constructing a largescale biochemical network based on a simulation-directed notation and its application to yeast cell cycle. Nucleic Acids Res 31: 4071-4084.
    • (2003) Nucleic Acids Res , vol.31 , pp. 4071-4084
    • Kurata, H.1    Matoba, N.2    Shimizu, N.3
  • 39
    • 18744387729 scopus 로고    scopus 로고
    • A grid layout algorithm for automatic drawing of biochemical networks
    • Li W, Kurata H (2005) A grid layout algorithm for automatic drawing of biochemical networks. Bioinformatics 21: 2036-2042.
    • (2005) Bioinformatics , vol.21 , pp. 2036-2042
    • Li, W.1    Kurata, H.2
  • 40
    • 49749109867 scopus 로고    scopus 로고
    • Visualizing Global Properties of Large Complex Networks
    • Li W, Kurata H (2008) Visualizing Global Properties of Large Complex Networks. PLoS One 3: e2541.
    • (2008) PLoS One , vol.3
    • Li, W.1    Kurata, H.2
  • 41
    • 67349186342 scopus 로고    scopus 로고
    • A spectral clustering-based framework for detecting community structures in complex networks
    • Jiang J, Dress A, Yang G (2009) A spectral clustering-based framework for detecting community structures in complex networks. Applied Mathematics Letters 22: 1479-1482.
    • (2009) Applied Mathematics Letters , vol.22 , pp. 1479-1482
    • Jiang, J.1    Dress, A.2    Yang, G.3


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