Protein-protein interactions: Making sense of networks via graph-theoretic modeling

BioEssays

Volumn 33, Issue 2, 2011, Pages 115-123

  Pržulj, Nataša ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

Graph algorithms; Network comparison and alignment; Network models; Protein function and disease; Protein protein interaction networks

Indexed keywords

PROTEIN;

ALGORITHM; BIOLOGY; COMMUNITY; GENOME; HUMAN; MATHEMATICAL MODEL; PROTEIN FUNCTION; PROTEIN PROTEIN INTERACTION; REVIEW; SCIENTIST;

ALGORITHMS; ANIMALS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; GENOME; HUMANS; MODELS, BIOLOGICAL; PROTEIN BINDING; PROTEIN INTERACTION DOMAINS AND MOTIFS; PROTEINS; RESEARCH DESIGN;

EID: 78651455332     PISSN: 02659247     EISSN: 15211878     Source Type: Journal    
DOI: 10.1002/bies.201000044     Document Type: Review

References (109)

1. Ito T, Tashiro K, Muta S, Ozawa R, et al. 2000. Toward a protein-protein interaction map of the budding yeast: A comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins. Proc Natl Acad Sci USA 97: 1143-7.
2. Uetz P, Giot L, Cagney G, Mansfield TA, et al. 2000. A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae Nature 403: 623-7.
3. Li S, Armstrong C, Bertin N, Ge H, et al. 2004. A map of the interactome network of the metazoan C. elegans Science 303: 540-3.
4. Giot L, Bader J, Brouwer C, Chaudhuri A, et al. 2003. A protein interaction map of Drosophila melanogaster Science 302: 1727-36.
5. Stelzl U, Worm U, Lalowski M, Haenig C, et al. 2005. A human protein-protein interaction network: A resource for annotating the proteome. Cell 122: 957-68.
6. Rual J-F, Venkatesan K, Hao T, Hirozane-Kishikawa T, et al. 2005. Towards a proteome-scale map of the human protein-protein interaction network. Nature 437: 1173-8.
7. Simonis N, Rual J-F, Carvunis A-R, Tasan M, et al. 2009. Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network. Nat Methods 6: 47-54.
8. Gavin AC, Bosche M, Krause R, Grandi P, et al. 2002. Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 415: 141-7.
9. Ho Y, Gruhler A, Heilbut A, Bader GD, et al. 2002. Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry. Nature 415: 180-3.
10. Gavin A, Aloy P, Grandi P, Krause R, et al. 2006. Proteome survey reveals modularity of the yeast cell machinery. Nature 440: 631-6.
11. Krogan N, Cagney G, Yu H, Zhong G, et al. 2006. Global landscape of protein complexes in the yeast Saccharomyces cerevisiae Nature 440: 637-43.
12. Tong AHY, Lesage G, Bader GD, Ding H, et al. 2004. Global mapping of the yeast genetic interaction network. Science 303: 808-13.
13. Rain J-D, Selig L, De Reuse H, Battaglia V, et al. 2001. The protein-protein interaction map of Helicobacter pylori Nature 409: 211-5.
14. Parrish JR, Yu J, Liu G, Hines JA, et al. 2007. A proteome-wide protein interaction map for Campylobacter jejuni Genome Biol 8: R130.
15. LaCount DJ, Vignali M, Chettier R, Phansalkar A, et al. 2005. A protein interaction network of the malaria parasite Plasmodium falciparum Nature 438: 103-7.
16. Chatr-aryamontri A, Ceol A, Peluso D, Nardozza A, et al. 2009. Virusmint: A viral protein interaction database. Nucleic Acids Res 37: D669-D673.
17. von Mering C, Krause R, Snel B, Cornell M, et al. 2002. Comparative assessment of large-scale data sets of protein-protein interactions. Nature 417: 399-403.
18. de Silva E, Stumpf M. 2005. Complex networks and simple models in biology. J R Soc Interface 2: 419-30.
19. Stumpf MPH, Wiuf C, May RM. 2005. Subnets of scale-free networks are not scale free: Sampling properties of networks. Proc Natl Acad Sci USA 102: 4221-4.
20. Han JDH, Dupuy D, Bertin N, Cusick ME, et al. 2005. Effect of sampling on topology predictions of protein-protein interaction networks. Nat Biotechnol 23: 839-44.
21. de Silva E, Thorne T, Ingram P, Agrafioti I, et al. 2006. The effects of incomplete protein interaction data on structural and evolutionary inferences. BMC Biol 4: 1-13.
22. Collins S, Kemmeren P, Zhao X-C, Greenblatt J, et al. 2007. Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae Mol Cell Proteomics 6: 439-50.
23. Hakes L, Pinney J, Robertson DL, Lovell SC. 2008. Protein-protein interaction networks and biology-what's the connection? Nat Biotechnol 26: 69-72.
24. Wodak S, Pu S, Vlasblom J, Seraphin B. 2009. Challenges and rewards of interaction proteomics. Mol Cell Proteomics 8: 3-18.
25. Jeong H, Tombor B, Albert R, Oltvai ZN, et al. 2000. The large-scale organization of metabolic networks. Nature 407: 651-4.
26. Tanaka R. 2005. Scale-rich metabolic networks. Phys Rev Lett 94: 168101.
27. Jeong H, Mason SP, Barabási A-L, Oltvai ZN. 2001. Lethality and centrality in protein networks. Nature 411: 41-2.
28. Coulomb S, Bauer M, Bernard D, Marsolier-Kergoat M-C. 2005. Gene essentiality and the topology of protein interaction networks. Proc Biol Sci B 272: 1721-5.
29. Song C, Havlin S, Makse HA. 2005. Self-similarity of complex networks. Nature 433: 392-5.
30. Itzkovitz S, Levitt R, Kashtan N, Milo R, et al. 2005. Coarse graining and self dissimilarity of complex networks. Phys Rev E 71: 016127.
31. Keller EF. 2005. Revisiting "scale-free" networks. BioEssays 27: 11060-8.
32. Han J-D, Bertin N, Hao T, Goldberg DS, et al. 2004. Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 430: 88-93.
33. Batada NN, Reguly T, Breitkreutz A, Boucher L, et al. 2006. Stratus not altocumulus: A new view of the yeast protein interaction network. PLoS Biol 4: e317.
34. Bertin N, Simonis N, Dupuy D, Cusick ME, et al. 2007. Confirmation of organized modularity in the yeast interactome. PLoS Biol 5: e153.
35. Batada NN, Reguly T, Breitkreutz A, Boucher L, et al. 2007. Still stratus not altocumulus: Further evidence against the date/party hub distinction. PLoS Biol 5: e154.
36. Huang S. 2004. Back to the biology in systems biology: What can we learn from biomolecular networks? Brief Funct Genomic Proteomic 2: 279-97.
37. Gunawardena J. 2010. Models in computational systems biology. In Lodhi HM, Muggleton SH ed; Elements of Computational Systems Biology, Wiley. p 65-90.
38. Keller EF. 2000. Models of and models for: Theory and practice in contemporary biology. Philos Sci 67: S72-S86.
39. Dougherty ER, Braga-Neto U. 2006. Epistemology of computational biology: Mathematical models and experimental prediction as the basis of their validity. J Biol Sys 14: 65-90.
40. Lappe M, Holm L. 2004. Unraveling protein interaction networks with near-optimal efficiency. Nat Biotechnol 22: 98-103.
41. Pržulj N, Corneil DG, Jurisica I. 2006. Efficient estimation of graphlet frequency distributions in protein-protein interaction networks. Bioinformatics 22: 974-80.
42. Kuchaiev O, Rasajski M, Higham D, Pržulj N. 2009. Geometric de-noising of protein-protein interaction networks. PLoS Comput Biol 5: e1000454.
43. Newman MEJ. 2003. The structure and function of complex networks. SIAM Rev 45: 167-256.
44. Barabási A-L, Albert R. 1999. Emergence of scaling in random networks. Science 286: 509-12.
45. Pržulj N, Corneil DG, Jurisica I. 2004. Modeling interactome: Scale-free or geometric? Bioinformatics 20: 3508-15.
46. Li L, Alderson D, Tanaka R, Doyle JC, et al. 2005. Towards a theory of scale-free graphs: Definition, properties, and implications. Internet Math 4: 431-523.
47. Watts DJ, Strogatz SH. 1998. Collective dynamics of 'small-world' networks. Nature 393: 440-2.
48. Milo R, Shen-Orr SS, Itzkovitz S, Kashtan N, et al. 2002. Network motifs: Simple building blocks of complex networks. Science 298: 824-7.
49. Shen-Orr SS, Milo R, Mangan S, Alon U. 2002. Network motifs in the transcriptional regulation network of Escherichia coli Nat Genet 31: 64-8.
50. Milo R, Itzkovitz S, Kashtan N, Levitt R, et al. 2004. Superfamilies of evolved and designed networks. Science 303: 1538-42.
51. Alon U. 2007. Network motifs: Theory and experimental approaches. Nat Rev Genet 8: 450-61.
52. Artzy-Randrup Y, Fleishman SJ, Ben-Tal N, Stone L. 2004. Comment on "Network motifs: Simple building blocks of complex networks" and "Superfamilies of evolved and designed networks". Science 305: 1107.
53. Brandstadt A, Van Bang L, Spinrad JP. 1999. Graph classes: A survey. Philadelphia, PA 19104-688: SIAM Monographs on Discrete Mathematics and Applications.
54. Pržulj N. 2007. Biological network comparison using graphlet degree distribution. Bioinformatics 23: e177-183.
55. Erdös P, Rényi A. 1959. On random graphs. Publicationes Mathematicae 6: 290-7.
56. Bollobas B. 1985. Random Graphs. Academic, London.
57. Newman MEJ, Strogatz SH, Watts DJ. 2001. Random graphs with arbitrary degree distributions and their applications. Phys Rev E 64: 026118-1.
58. Aiello W, Chung F, Lu L. 2001. A random graph model for power law graphs. Exp Math 10: 53-66.
59. Wagner A. 2003. How the global structure of protein interaction networks evolves. Proc Biol Sci 270: 457-66.
60. Pastor-Satorras R, Smith E, Sole RV. 2003. Evolving protein interaction networks through gene duplication. J Theor Biol 222: 199-210.
61. Kuchaiev O, Pržulj N. 2009. Learning the structure of protein-protein interaction networks. 2009 Pacific Symposium on Biocomputing (PSB).
62. Pržulj N, Kuchaiev O, Stevanovic A, Hayes W. 2010. Geometric evolutionary dynamics of protein interaction networks. 2010 Pacific Symposium on Biocomputing (PSB).
63. MemiseviĆ V, MilenkoviĆ T, Pržulj N. 2010. An integrative approach to modeling biological networks. J Integr Bioinform 7: 120.
64. Higham D, Rašajski M, Pržulj N. 2008. Fitting a geometric graph to a protein-protein interaction network. Bioinformatics 24: 1093-9.
65. Sharan R, Ideker T. 2006. Modeling cellular machinery through biological network comparison. Nat Biotechnol 24: 427-33.
66. Venkatesan K, Rual J-F, Vazquez A, Stelzl U, et al. 2009. An empirical framework for binary interactome mapping. Nat Methods 6: 83-90.
67. Kelley BP, Bingbing Y, Lewitter F, Sharan R, et al. 2004. Path-BLAST: A tool for alignment of protein interaction networks. Nucleic Acids Res 32: 83-8.
68. Berg J, Lassig M. 2004. Local graph alignment and motif search in biological networks. Proc Natl Acad Sci USA 101: 14689-94.
69. Flannick J, Novak A, Balaji S, Harley H, et al. 2006. Graemlin general and robust alignment of multiple large interaction networks. Genome Res 16: 1169-81.
70. Berg J, Lassig M. 2006. Cross-species analysis of biological networks by Bayesian alignment. Proc Natl Acad Sci USA 103: 10967-72.
71. Sharan R, Suthram S, Kelley RM, Kuhn T, et al. 2005. Conserved patterns of protein interaction in multiple species. Proc Natl Acad Sci USA 102: 1974-9.
72. Koyutürk M, Kim Y, Topkara U, Subramaniam S, et al. 2006. Pairwise alignment of protein interaction networks. J Comput Biol 13: 182-99.
73. Singh R, Xu J, Berger B. 2007. Pairwise global alignment of protein interaction networks by matching neighborhood topology. In Research in Computational Molecular Biology. Springer. p 16-31.
74. Flannick J, Novak AF, Do CB, Srinivasan BS, et al. 2008. Automatic parameter learning for multiple network alignment. Proceedings of RECOMB, 214-31.
75. Singh R, Xu J, Berger B. 2008. Global alignment of multiple protein interaction networks. 2008 Pacific Symposium on Biocomputing (PSB), p. 303-314.
76. Zaslavskiy M, Bach F, Vert JP. 2009. Global alignment of protein-protein interaction networks by graph matching methods. Bioinformatics 25: i259-267.
77. Liao C-S, Lu K, Baym M, Singh R, et al. 2009. IsoRankN: Spectral methods for global alignment of multiple protein networks. Bioinformatics 25: i253-258.
78. Kuchaiev O, Milenkovic T, Memisevic V, Hayes W, et al. 2010. Topological network alignment uncovers biological function and phylogeny. J R Soc Interface 7: 1341-54.
79. Milenkovic T, Ng WL, Hayes W, Pržulj N. 2010. Optimal network alignment with graphlet degree vectors. Cancer Inform 9: 121-37.
80. Altschul SF, Gish W, Miller W, Lipman DJ. 1990. Basic local alignment search tool. J Mol Biol 215: 403-10.
81. Bruckner S, Huffner F, Karp RM, Shamir R, et al. 2009. Topology-free querying of protein interaction networks. Proceedings of RECOMB 2009 5541 of LNCS: 74-89.
82. MilenkoviĆ T, Pržulj N. 2008. Uncovering biological network function via graphlet degree signatures. Cancer Inform 6: 257-73.
83. MemiseviĆ V, MilenkoviĆ T, Pržulj N. 2010. Complementarity of network and sequence information in homologous proteins. J Integr Bioinform 7: 135.
84. Sharan R, Ulitsky I, Shamir R. 2007. Network-based prediction of protein function. Mol Syst Biol 3: 1-13.
85. Sharan R, Ideker T. 2008. Protein networks in disease. Genome Res 18: 644-52.
86. Yu H, Braun P, Yildirim MA, Lemmens I, et al. 2008. High-quality binary protein interaction map of the yeast interactome networks. Science 322: 104-10.
87. Reguly T, Breitkreutz A, Boucher L, Breitkreutz BJ, et al. 2006. Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae J Biol 5: 11.
88. Ratmann O, Wiuf C, Pinney JW. 2009. From evidence to inference: Probing the evolution of protein interaction networks. HFSP J 3: 290-306.
89. Pržulj N, Wigle D, Jurisica I. 2004. Functional topology in a network of protein interactions. Bioinformatics 20: 340-8.
90. Cusick ME, Yu H, Smolyar A, Venkatesan K, et al. 2009. Literature curated protein interaction datasets. Nat Methods 6: 39-46.
91. Bader GD, Hogue CWV. 2002. Analyzing yeast protein-protein interaction data obtained from different sources. Nat Biotechnol 20: 991-7.
92. Hishigaki H, Nakai K, Ono T, Tanigami A, et al. 2001. Assessment of prediction accuracy of protein function from protein-protein interaction data. Yeast 18: 523-31.
93. Schwikowski B, Uetz P, Fields A. 2000. A network of protein-protein interactions in yeast. Nat Biotechnol 18: 1257-61.
94. Chua H, Sung W, Wong L. 2006. Exploiting indirect neighbours and topological weight to predict protein function from protein-protein interactions. Bioinformatics 22: 1623-30.
95. Vazquez A, Flammini A, Maritan A, Vespignani A. 2003. Global protein function prediction from protein-protein interaction networks. Nat Biotechnol 21: 697-700.
96. Karaoz U, Murali T, Letovsky S, Zheng Y, et al. 2004. Whole-genome annotation by using evidence integration in functional-linkage networks. Proc Natl Acad Sci USA 101: 2888-93.
97. Nabieva E, Jim K, Agarwal A, Chazelle B, et al. 2005. Whole-proteome prediction of protein function via graph-theoretic analysis of interaction maps. Bioinformatics 21: i302-310.
98. Bader GD, Hogue CWV. 2003. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4: 2.
99. Sharan R, Ideker T, Kelley BP, Shamir R, et al. 2004. Identification of protein complexes by comparative analysis of yeast and bacterial protein interaction data. Proceedings of RECOMB, 2004: 282-9.
100. King AD, Pržulj N, Jurisica I. 2004. Protein complex prediction via cost-based clustering. Bioinformatics 20: 3013-20.
101. Jung SH, Hyun B, Jang W.-H, Hur H.-Y, et al. 2010. Protein complex prediction based on simultaneous protein interaction network. Bioinformatics 26: 385-91.
102. Kaake RM, MilenkoviĆ T, Pržulj N, Kaiser P, et al. 2010. Characterization of cell cycle specific protein interaction networks of the yeast 26s proteasome complex by the QTAX strategy. J Proteome Res 9: 2016-29.
103. Guerrero C, MilenkoviĆ T, Pržulj N, Kaiser P, et al. 2008. Characterization of the proteasome interaction network using a QTAX-based tag-team strategy and protein interaction network analysis. Proc Natl Acad Sci USA 105: 13333-8.
104. MilenkoviĆ T, MemiseviĆ V, Ganesan AK, Pržulj N. 2010. Systems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related interaction networks. J R Soc Interface 7: 423-37.
105. Wachi S, Yoneda K, Wu R. 2005. Interactome-transcriptome analysis reveals the high centrality of genes differentially expressed in lung cancer tissues. Bioinformatics 21: 4205-8.
106. Jonsson PF, Bates PA. 2006. Lobal topological features of cancer proteins in the human interactome. Bioinformatics 22: 2291-7.
107. Goh KI, Cusick ME, Valle D, Childs B, et al. 2007. The human disease network. Proc Natl Acad Sci USA 104: 8685-90.
108. Vanunu O, Magger O, Ruppin E, Shlomi T, et al. 2010. Associating genes and protein complexes with disease via network propagation. PLoS Comput Biol 6: e1000641.
109. Aragues R, Sander C, Oliva B. 2008. Predicting cancer involvement of genes from heterogeneous data. BMC Bioinformatics 9: 172.