SCPS: A fast implementation of a spectral method for detecting protein families on a genome-wide scale

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Nepusz, Tamás ^a   Sasidharan, Rajkumar ^b   Paccanaro, Alberto ^a  

^a UNIVERSITY OF LONDON   (United Kingdom)

^b GEOPHYSICAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL BIOLOGY; CONNECTED COMPONENT ANALYSIS; FAST IMPLEMENTATION; GRAPHICAL REPRESENTATIONS; HIER-ARCHICAL CLUSTERING; SEQUENCE INFORMATIONS; SPECTRAL CLUSTERING METHODS; YEAST SACCHAROMYCES CEREVISIAE;

BIOINFORMATICS; CLUSTERING ALGORITHMS; COMPUTER OPERATING SYSTEMS; GENES; SPECTROSCOPY; TOOLS; YEAST;

PROTEINS;

SACCHAROMYCES CEREVISIAE;

PROTEIN;

AMINO ACID SEQUENCE; ARTICLE; AUTOMATED PATTERN RECOGNITION; CHEMISTRY; CLUSTER ANALYSIS; COMPUTER PROGRAM; FUNGAL GENOME; GENETICS; GENOMICS; METHODOLOGY; PROTEIN DATABASE; SACCHAROMYCES CEREVISIAE; SEQUENCE ANALYSIS;

AMINO ACID SEQUENCE; CLUSTER ANALYSIS; DATABASES, PROTEIN; GENOME, FUNGAL; GENOMICS; PATTERN RECOGNITION, AUTOMATED; PROTEINS; SACCHAROMYCES CEREVISIAE; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE;

EID: 77950430912     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-120     Document Type: Article

References (29)

1. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990, 215(3):403-410.
2. Enright AJ, Ouzounis CA. GeneRAGE: a robust algorithm for sequence clustering and domain detection. Bioinformatics 2000, 16(5):451-457. 10.1093/bioinformatics/16.5.451, 10871267.
3. Pipenbacher P, Schliep A, Schneckener S, Schönhuth A, Schomburg D, Schrader R. ProClust: improved clustering of protein sequences with an extended graph-based approach. Bioinformatics 2002, 18:S182-S191. 10.1093/bioinformatics/18.1.182, 12386002.
4. Paccanaro A, Casbon JA, Saqi MAS. Spectral clustering of protein sequences. Nucleic Acids Res 2006, 34(5):1571-1580. 10.1093/nar/gkj515, 1409676, 16547200.
5. Everitt B. Cluster analysis 1993, London: Edward Arnold, 3.
6. Ballard D, Brown C. Computer Vision 1982, Englewood Cliffs: Prentice-Hall.
7. Enright AJ, Van Dongen S, Ouzounis CA. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res 2002, 30(7):1575-1584. 10.1093/nar/30.7.1575, 101833, 11917018.
8. Kannan N, Vishveshwara S. Identification of side-chain clusters in protein structures by a graph spectral method. J Mol Biol 1999, 292(2):441-464. 10.1006/jmbi.1999.3058, 10493887.
9. Forman JJ, Clemons PA, Schreiber SL, Haggarty SJ. SpectralNET - an application for spectral graph analysis and visualization. BMC Bioinformatics 2005, 6:260. 10.1186/1471-2105-6-260, 1276787, 16236170.
10. Krishnadev O, Brinda K, Vishveshwara S. A graph spectral analysis of the structural similarity network of protein chains. Proteins Struct Funct Bioinfo 2005, 61:152-163.
11. Verkhedkar K, Raman K, Chandra N, Vishveshwara S. Metabolome based reaction graphs of M. tuberculosis and M. leprae: a comparative network analysis. PLoS ONE 2007, 2(9):e881. 10.1371/journal.pone.0000881, 1964534, 17849010.
12. Wang G, Shen Y, Ouyang M. A vector partitioning approach to detecting community structure in complex networks. Comput Math Appl 2008, 55(12):2746-2752.
13. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003, 13(11):2498-504. 10.1101/gr.1239303, 403769, 14597658.
14. Meilǎ M, Shi J. A random walks view of spectral segmentation. Proceedings of the 8th International Workshop on Artificial Intelligence and Statistics (AISTATS) 2001,
15. Ng AY, Jordan MI, Weiss Y. On Spectral Clustering: Analysis and an algorithm. Advances in Neural Information Processing Systems 14 2001, 849-856. MIT Press.
16. van Dongen S. Performance criteria for graph clustering and Markov cluster experiments. Tech Rep INS-R0012 2000,
17. Newman M. Fast algorithm for detecting community structure in networks. Phys Rev E 2004, 69(6):066133.
18. Fruchterman T, Reingold E. Graph drawing by force directed placement. Software Pract Ex 1991, 21(11):1129-1164.
19. Lehoucq RB, Sorensen DC, Yang CY. ARPACK users' guide: solution of large-scale eigenvalue problems with implicitly restarted Arnoldi methods 1998, SIAM.
20. Murzin A, Brenner S, Hubbard T, Chothia C. SCOP - a structural classification of proteins database for the investigation of sequences and structures. J Mol Biol 1995, 247(4):536-540.
21. Chandonia JM, Hon G, Walker NS, Lo Conte L, Koehl P, Levitt M, Brenner SE. The ASTRAL Compendium in 2004. Nucleic Acids Res 2004, (32 Database):D189-92. 10.1093/nar/gkh034, 308768, 14681391.
22. Jensen LJ, Kuhn M, Stark M, Chaffron S, Creevey C, Muller J, Doerks T, Julien P, Roth A, Simonovic M, Bork P, von Mering C. STRING 8 - a global view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res 2009, (37 Database):D412-416. 10.1093/nar/gkn760, 2686466, 18940858.
23. Hong EL, Balakrishnan R, Dong Q, Christie KR, Park J, Binkley G, Costanzo MC, Dwight SS, Engel SR, Fisk DG, Hirschman JE, Hitz BC, Krieger CJ, Livstone MS, Miyasato SR, Nash RS, Oughtred R, Skrzypek MS, Weng S, Wong ED, Zhu KK, Dolinski K, Botstein D, Cherry JM. Gene Ontology annotations at SGD: new data sources and annotation methods. Nucleic Acids Res 2008, 36:D577-581. 10.1093/nar/gkm909, 2238894, 17982175.
24. Altschul SF, Madden TL, Schffer AA, Schffer RA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25:3389-3402. 10.1093/nar/25.17.3389, 146917, 9254694.
25. Biegert A, Soding J. Sequence context-specific profiles for homology searching. Proc Natl Acad Sci USA 2009, 106(10):3770-3775. 10.1073/pnas.0810767106, 2645910,2645910, 19234132.
26. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G. Gene ontology: tool for the unification of biology. Nat Genet 2000, 25:25-29. 10.1038/75556, 10802651.
27. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc B Stat Meth 1995, 57:289-300.
28. Ruepp A, Zollner A, Maier D, Albermann K, Hani J, Mokrejs M, Tetko I, Guldener U, Mannhaupt G, Munsterkotter M, Mewes HW. The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes. Nucl Acids Res 2004, 32(18):5539-5545. 10.1093/nar/gkh894, 524302, 15486203.
29. Arthur D, Vassilvitskii S. How slow is the k-means method?. SCG '06: Proceedings of the 22nd Annual Symposium on Computational Geometry 2006, 144-153. New York, NY, USA: ACM.