Revealing biological modules via graph summarization

Journal of Computational Biology

Volumn 16, Issue 2, 2009, Pages 253-264

  Navlakha, Saket ^a   Schatz, Michael C ^a   Kingsford, Carl ^a,b  

^a University of Maryland ^*  (United States)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

Function prediction; Graph summarization; Module detection; Protein interaction networks

Indexed keywords

ALGORITHM; ARTICLE; COMPLEX FORMATION; PRIORITY JOURNAL; PROTEIN INTERACTION;

ALGORITHMS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; COMPUTER GRAPHICS; COMPUTER SIMULATION; DATABASES, PROTEIN; MODELS, BIOLOGICAL; PROTEIN INTERACTION MAPPING;

EID: 59649120244     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2008.11TT     Document Type: Article

References (45)

1. Ashburner, M., Ball, C.A., Blake, J.A., et al. 2000. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25-29.
2. Bader, G.D., and Hogue, C.W.V. 2003. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinform. 4, 2.
3. Brohee, S., and van Helden, J. 2006. Evaluation of clustering algorithms for protein-protein interaction networks. BMC Bioinform. 7, 488.
4. Brun, C., Chevenet, F., Martin, D., et al. 2003. Functional classification of proteins for the prediction of cellular function from a protein-protein interaction network. Genome Biol. 5, R6.
5. Bu, D., Zhao, Y., Cai, L., et al. 2003. Topological structure analysis of the protein-protein interaction network in budding yeast. Nucleic Acids Res. 31, 2443-2450.
6. Cherry, J.M., Ball, C., Weng, S., et al. 1997. Genetic and physical maps of Saccharomyces cerevisiae. Nature 387, 67-73.
7. Clauset, A., Newman, M.E.J., and Moore, C. 2004. Finding community structure in very large networks. Phys. Rev. E 70, 066111.
8. Enright, A.J., Van Dongen, S., and Ouzounis, C.A. 2002. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res. 30, 1575-1584.
9. Fields, S., and Song, O. 1989. A novel genetic system to detect protein-protein interactions. Nature 340, 245-246.
10. Fortunato, S., and Barthelemy, M. 2007. Resolution limit in community detection. Proc. Natl. Acad. Sci. USA 104, 36-41.
11. Gavin, A.-C., Aloy, P., Grandi, P., et al. 2006. Proteome survey reveals modularity of the yeast cell machinery. Nature 440, 631-636.
12. Guimera, R., and Luis, L.A.N. 2005. Functional cartography of complex metabolic networks. Nature 433, 895-900.
13. Guldener, U., Munsterkotter, M., Kastenmuller, G., et al. 2005. CYGD: the comprehensive yeast genome database. Nucleic Acids Res. 33, D364.
14. Han, J.-D.J., Bertin, N., Hao, T., et al. 2004. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 430, 88-93.
15. Hart, T.G., Ramani, A.K., and Marcotte, E.M. 2006. How complete are current yeast and human protein-interaction networks? Genome Biol. 7, 120.
16. Hartwell, L.H., Hopfield, J.J., Leibler, S., et al. 1999. From molecular to modular cell biology. Nature 402, C47-C52.
17. Jansen, R., Yu, H., Greenbaum, D., et al. 2003. A bayesian networks approach for predicting protein-protein interactions from genomic data. Science 302, 449-453.
18. Kerrien, S., Alam-Faruque, Y., Aranda, B., et al. 2007. Intact-open source resource for molecular interaction data. Nucleic Acids Res. 35, D561-D565.
19. King, A.D., Przulj, N., and Jurisica, I. 2004. Protein complex prediction via cost-based clustering. Bioinformatics 20, 3013-3020.
20. Krogan, N.J., Cagney, G., Yu, H., et al. 2006. Global landscape of protein complexes in the yeast Saccharomyces cerevisiae. Nature 440, 637-643.
21. Kumar, R., Raghavan, P., Rajagopalan, S., et al. 1999. Trawling the web for emerging cyber-communities. Comput. Netw. 31, 1481-1493.
22. Myers, C.L., Barrett, D.R., Hibbs, M.A., et al. 2006. Finding function: evaluation methods for functional genomic data. BMC Genomics 7, 187.
23. Navlakha, S., Rastogi, R., and Shrivastava, N. 2008. Graph summarization with bounded error. SIGMOD 2008 419-432.
24. Newman, M.E.J. 2006. Modularity and community structure in networks. Proc. Natl. Acad. Sci. USA 103, 8577-8582.
25. Newman, M.E.J., and Girvan, M. 2004. Finding and evaluating community structure in networks. Phys. Rev. E 69.
26. Przulj, N., Wigle, D.A., and Jurisica, I. 2004. Functional topology in a network of protein interactions. Bioinformatics 20, 340-348.
27. Qiu, J., and Noble, W.S. 2008. Predicting co-complexed protein pairs from heterogeneous data. PLoS Comput. Biol. 4.
28. Radicchi, F., Castellano, C., Cecconi, F., et al. 2004. Defining and identifying communities in networks. Proc. Natl. Acad. Sci. USA 101, 2658-2663.
29. Rissanen, J. 1978. Modeling by shortest data description. Automatica 14, 465-471.
30. Rives, A.W., and Galitski, T. 2003. Modular organization of cellular networks. Proc. Natl. Acad. Sci. USA 100, 1128-1133.
31. Rosvall, M., and Bergstrom, C.T. 2007. An information-theoretic framework for resolving community structure in complex networks. Proc. Natl. Acad. Sci. USA 104, 7327-7331.
32. Samanta, M.P., and Liang, S. 2003. Predicting protein functions from redundancies in large-scale protein interaction networks. Proc. Natl. Acad. Sci. USA 100, 12579-12583.
33. Shannon, P., Markiel, A., Ozier, O., et al. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498-2504.
34. Sharan, R., Ulitsky, I., and Shamir, R. 2007. Network-based prediction of protein function. Nat. Mol. Syst. Biol. 3, 88.
35. Shoemaker, B.A., and Panchenko, A.R. 2007. Deciphering protein-protein interactions. Part I. Experimental techniques and databases. PLoS Comput. Biol. 3, e42.
36. Spirin, V., and Mirny, L.A. 2003. Protein complexes and functional modules in molecular networks. Proc. Natl. Acad. Sci. USA 100, 12123-12128.
37. Tanay, A., Sharan, R., Kupiec, M., et al. 2004. Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data. Proc. Natl. Acad. Sci. USA 101, 2981-2986.
38. Troyanskaya, O.G., Dolinski, K., Owen, A.B., et al. 2003. A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae). Proc. Natl. Acad. Sci. USA 100, 8348-8353.
39. Ulitsky, I., and Shamir, R. 2007. Identification of functional modules using network topology and high-throughput data. BMC Syst. Biol. 1, 8.
40. van Dongen, S. 1998. A new cluster algorithm for graphs, T.R. 9814, Centrum voor Wiskunde en Informatica (CWI).
41. Wakita, K., and Tsurumi, T. 2007. Finding community structure in mega-scale social networks. arXiv:cs/0702048v1.
42. Wang, C., Ding, C., Yang, Q., et al. 2007. Consistent dissection of the protein interaction network by combining global and local metrics. Genome Biol. 8, R271.
43. Yu, H., Paccanaro, A., Trifonov, V., et al. 2006. Predicting interactions in protein networks by completing defective cliques. Bioinformatics 22, 823-829.
44. Zhu, X., Gerstein, M., and Snyder, M. 2007. Getting connected: analysis and principles of biological networks. Genes Dev. 21, 1010-1024.
45. Ziv, E., Middendorf, M., and Wiggins, C.H. 2005. Information-theoretic approach to network modularity. Phys. Rev. E 71, 046117.