NETAL: A new graph-based method for global alignment of protein-protein interaction networks

Bioinformatics

Volumn 29, Issue 13, 2013, Pages 1654-1662

  Neyshabur, Behnam ^a   Khadem, Ahmadreza ^a   Hashemifar, Somaye ^b   Arab, Seyed Shahriar ^c,d  

^a SHARIF UNIVERSITY OF TECHNOLOGY   (Iran)

^b UNIVERSITY OF TEHRAN   (Iran)

^c TARBIAT MODARES UNIVERSITY   (Iran)

^d INSTITUTE FOR STUDIES IN THEORETICAL PHYSICS AND MATHEMATICS IPM   (Iran)

Author keywords

[No Author keywords available]

Indexed keywords

SACCHAROMYCES CEREVISIAE PROTEIN;

ALGORITHM; ARTICLE; COMPUTER GRAPHICS; COMPUTER PROGRAM; HUMAN; METABOLISM; METHODOLOGY; PROTEIN ANALYSIS; SEQUENCE ALIGNMENT; PROCEDURES;

ALGORITHMS; COMPUTER GRAPHICS; HUMANS; PROTEIN INTERACTION MAPPING; SACCHAROMYCES CEREVISIAE PROTEINS; SEQUENCE ALIGNMENT; SOFTWARE;

EID: 84879967643     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btt202     Document Type: Conference Paper

References (33)

1. Aebersold, R. and Mann, M. (2003) Mass spectrometry-based proteomics. Nature, 422, 198-207.
2. Andersen, R. et al. (2006) Local graph partitioning using page rank vectors. In: Foundations of Computer Science. IEEE Computer Society, Los Alamitos, CA, USA, pp. 475-486.
3. Berg, J. et al. (2004) Structure and evolution of protein interaction networks: A statistical model for link dynamics and gene duplications. BMC Evol. Biol., 4, 51.
4. Chindelevitch, L. et al. (2010) Local optimization for global alignment of protein interaction networks. Pac. Symp. Biocomput., 2010, 123-132.
5. Collins, S.R. et al. (2007) Toward a comprehensive atlas of the physical interactome of Saccharomyces cerevisiae. Mol. Cell Proteomics, 6, 439-450.
6. Flannick, J. et al. (2006) Graemlin: General and robust alignment of multiple large interaction networks. Genome Res., 16, 1169-1181.
7. Flannick, J. et al. (2008) Automatic parameter learning for multiple network alignment. In: Research in Computational Molecular Biology, Lecture Notes in Computer Science. Vol. 4955, Springer, Berlin/Heidelberg, pp. 214-231.
8. Fossum, E. et al. (2009) Evolutionarily conserved herpes viral protein interaction networks. PLoS Pathog., 5, e1000570.
9. Giot, L. et al. (2003) A protein interaction map of Drosophila melanogaster. Science, 302, 1727-1736.
10. Kayarkar, N.A. et al. (2009) Protein network in diseases. Int. J. Drug Discov., 1, 10-17.
11. Kelley, B.P. et al. (2003) Conserved pathways within bacteria and yeast as revealed by global protein network alignment. Proc. Natl Acad. Sci. USA, 100, 11394-11399.
12. Kelley, B. et al. (2004) PathBLAST: A tool for alignment of protein interaction networks. Nucl. Acids Res., 32, 83-88.
13. Kerrien, S. et al. (2012) The IntAct molecular interaction database in 2012. BMC Bioinformatics, 40, D841-D846.
14. Klau, G. (2009) A new graph-based method for pairwise global network alignment. BMC Bioinformatics, 10, S59.
15. Koyuturk, M. et al. (2006) Pairwise alignment of protein interaction networks. J. Comput. Biol., 13, 182-199.
16. Kuchaiev, O. et al. (2010) Topological network alignment uncovers biological function and phylogeny. J. R. Soc. Interface, 7, 1341-1354.
17. Kuchaiev, O. and Przulj, N. (2011) Integrative network alignment reveals large regions of global network similarity in yeast and human. Bioinformatics, 27, 1390-1396.
18. Milenkovic, T. et al. (2010) Optimal network alignment with graphlet degree vectors. Cancer Informat., 9, 121-137.
19. Mills-Tettey, G.A. et al. (2007) The dynamic Hungarian algorithm for the assignment problem with changing costs. Robotics Institute, Technical Report CMURI-TR-07-2.
20. Parrish, J.R. et al. (2007) A proteome-wide protein interaction map for Campylobacter jejuni. Genome Biol., 8, R130.
21. Radivojac, P. et al. (2008) An integrated approach to inferring gene-disease associations in humans. Proteins, 72, 1030-1037.
22. Rzhetsky, A. and Gomez, S.M. (2001) Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome. Bioinformatics, 17, 988-996.
23. Sharan, R. et al. (2005) Conserved patterns of protein interaction in multiple species. PNAS, 102, 1974-1979.
24. Singh, R. et al. (2007) Pairwise global alignment of protein interaction networks by matching neighborhood topology. In: Research in Computational Molecular Biology, Vol. 4453, Lecture Notes in Computer Science. Springer, Berlin/Heidelberg, p. 1631.
25. Singh, R. et al. (2008) Global alignment of multiple protein interaction networks. Proc. Paci. Symposium on Biocomputing, 13, 303-314.
26. Singh, R. et al. (2008) Global alignment of multiple protein interaction networks with application to functional orthology detection. Proc. Natl Acad. of Sci. USA, 105, 12763-12768.
27. Stelzl, U. et al. (2005) A human protein-protein interaction network: A resource for annotating the proteome. Cell, 122, 957-968.
28. The Gene Ontology Consortium. (2000) Gene ontology: Tool for the unification of biology. Nat. Genet., 25, 25-29.
29. Tian, W. and Samatova, N. (2009) Pairwise alignment of interaction networks by fast identication of maximal conserved patterns. In: Pacific Symposium on Biocomputing. pp. 99-110.
30. von Mering, C. et al. (2002) Comparative assessment of large-scale data sets of protein-protein interactions. Nature, 417, 399-403.
31. Wagner, A. (2001) The yeast protein interaction network evolves rapidly and contains few redundant duplicate genes. Molecular Biology and Evolution, 18, 1283-1292.
32. Zaslavskiy, M. et al. (2009) Global alignment of protein-protein interaction networks by graph matching methods. Bioinformatics, 25, i259-i267.
33. Schlicker et al. (2006) A new measure for functional similarity of gene products based on Gene Ontology. BMC Bioinformatics, 7, 302.