Joint clustering of protein interaction networks through Markov random walk

BMC Systems Biology

Volumn 8, Issue 1, 2014, Pages

  Wang, Yijie ^a   Qian, Xiaoning ^a,b,c  

^a Department of Electrical and Computer Engineering   (United States)

^b University of South Florida   (United States)

^c UNIVERSITY OF SOUTH FLORIDA   (United States)

Author keywords

Joint Clustering Algorithm; Markov Random Walk; Protein Protein Interaction Networks

Indexed keywords

ALGORITHM; ARTICLE; BIOLOGY; CLUSTER ANALYSIS; GENE ONTOLOGY; GENETICS; HUMAN; METABOLISM; METHODOLOGY; PROBABILITY; PROTEIN ANALYSIS; SACCHAROMYCES CEREVISIAE; SEQUENCE HOMOLOGY;

ALGORITHMS; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; GENE ONTOLOGY; HUMANS; MARKOV CHAINS; PROTEIN INTERACTION MAPPING; SACCHAROMYCES CEREVISIAE; SEQUENCE HOMOLOGY, AMINO ACID;

EID: 84910122557     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/1752-0509-8-S1-S9     Document Type: Article

References (31)

1. Butland G, Peregrin-Alvarez J, Li J, et al.: Interaction network containing conserved and essential protein complexes in Escherichia coli. Nature. 2005, 433: 531-537. 10.1038/nature03239.
2. Kelley R, Ideker T: Systematic interpretation of genetic interactions using protein networks. Nat Biotech. 2005, 23: 561-566. 10.1038/nbt1096.
3. Raman K: Construction and analysis of protein-protein interaction networks. Automated Experimentation. 2010, 2 (2):
4. Zhang L, Zhang Y, Adusumilli S, et al.:: Molecular interactions that enable movement of the lyme disease agent from the tick gut into the hemolymph. PLoS Pathog. 2011, 7 (6): 1002079-10.1371/journal.ppat.1002079.
5. Wang Q, Feng J, Wang J, et al.:: Disruption of tab1/p38[alpha] interaction using a cell-permeable peptide limits myocardial ischemia/reperfusion injury. Molecular Therapy advance online publication. 2013
6. Pereira-Leal J, Enright A, Ouzounis C: Detection of functional modules from protein interaction networks. Proteins. 2004, 54 (1): 49-57.
7. Spirin V, Mirny L: Protein complexes and functional modules in molecular networks. Proc Natl Acad Sci USA. 2003, 100: 12123-12128. 10.1073/pnas.2032324100.
8. Poyatos J, Hurst L: How biologically relevant are interaction-based modules in protein networks?. Genome Biol. 2004, 5: 93-10.1186/gb-2004-5-11-r93.
9. Bernardo DD, Gardner T, Collins J: Robust identification of large genetic networks. Pac Symp Biocomput. 2004, 9: 486-497.
10. Kolker E, Makarova K, Shabalina S, et al.:: Identification and functional analysis of 'hypothetical' genes expressed in Haemophilus influenzae. Nucleic Acids Res. 2004, 32 (8): 2353-2361. 10.1093/nar/gkh555.
11. Shi J, Malik J: Normalized cuts and image segmentation. IEEE Trans. on Pattern Analysis and Machine Intelligence. 2000, 22 (8):
12. Wang Y, Qian X: Functional module identification in protein interaction networks by interaction patterns. Bioinformatics. 2013
13. Xing E, Jordan M: On semidefinite relaxation for normalized k-cut and connections to spectral clustering. Technical report, UC. Berkeley. 2003
14. Dongen SV: A cluster algorithm for graphs. Technical Report INS-R0010. 2000
15. Satuluri V, Parthasarathy S: Scalable Graph Clustering Using Stochastic Flows: Applications to Community Discovery. 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'09). 2009
16. Satuluri V, Parthasarathy S, Ucar D: Markov Clustering of Protein Interaction Networks. ACM Conference on Bioinformatics, Computational Biology and Biomedicine 2010. 2010
17. DIttrich MT, Klau GW, Rosenwald A, Dandekar T, Muller T: Identifying functional modules in protein-protein interaction networks: an integrated exact approach. Bioinformatics. 2007, 24 (13): 223-231.
18. Ciriello G, Mina M, Guzzi PH, Cannataro M, Guerra C: Alignnemo: A local network alignment method to integrate homology and topology. PLoS ONE. 2012, 7 (6): 38107-10.1371/journal.pone.0038107.
19. Ashburner M, Ball C, Blake J, et al.:: Gene ontology: Tool for the unification of biology. the gene ontology consortium. Nat Genet. 2000, 25 (1): 25-29. 10.1038/75556.
20. Altschul S, Gish W, Miller W, Myers E, Lipman D: Basic local alignment search tool. J Mol Biol. 1990, 215 (3): 403-410.
21. Satuluri V, Parthasarathy S: Symmetrizations for Clustering Directed Graphs. 14th International Conference on Extending Database Technology (EDBT11). 2011
22. Salwinski L, Miller C, Smith A, Pettit F, JU JB, Eisenberg D: The Database of Interacting Proteins: 2004 update. Nucleic Acids Research. 2004, 32: 449-451.
23. Breitkreutz B, Stark C, et al.:: The BioGRID Interaction Database: 2008 update. Nucleic Acids Res. 2008, 36: 637-640.
24. Prasad T, et al.:: Human Protein Reference Database--2009 update. Nucleic Acids Research. 2009, 37: 767-772. 10.1093/nar/gkn892.
25. McDowall M, Scott M, Barton G: Pips: Human protein-protein interactions prediction database. Nucleic Acids Research. 2009, 37: 651-656. 10.1093/nar/gkn870.
26. Hong E, et al.:: Gene ontology annotations at sgd: New data sources and annotation methods. Nucleic Acids Res. 2008, 36: 577-581.
27. Ruepp A, Brauner B, Dunger-Kaltenbach I, et al.:: Corum: The comprehensive resource of mammalian protein complexes. Nucl Acids Res. 2008, 36: 646-650.
28. Shih Y, Parthasarathy S: Identifying functional modules in interaction networks through overlapping markov clustering. Bioinformatics. 2012, 28: 473-479. 10.1093/bioinformatics/bts370.
29. Shih Y, Parthasarathy S: Scalable global alignment for multiple biological networks. BMC Bioinformatics. 2012, 13 (Suppl 3): 11-10.1186/1471-2105-13-S3-S11.
30. Maslov S, Sneppen K: Specificity and stability in topology of protein networks. Science. 2002, 296: 910-913. 10.1126/science.1065103.
31. Lancichinetti A, Fortunato S, Jnos K: Detecting the overlapping and hierarchical community structure in complex networks. New Journal of Physics. 2009, 11 (3): 033015-10.1088/1367-2630/11/3/033015.