KABOOM! A new suffix array based algorithm for clustering expression data

Bioinformatics

Volumn 27, Issue 24, 2011, Pages 3348-3355

  Hazelhurst, Scott ^a   Lipták, Zsuzsanna ^b  

^a UNIVERSITY OF THE WITWATERSRAND   (South Africa)

^b UNIVERSITY OF SALERNO   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGY; CLUSTER ANALYSIS; COMPUTER PROGRAM; ECONOMICS; GENE EXPRESSION PROFILING; HUMAN; METHODOLOGY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; GENE EXPRESSION PROFILING; HUMANS; SOFTWARE;

EID: 83355177241     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btr560     Document Type: Article

References (27)

1. Burkhardt, S. et al. (1999) q-gram based database searching using a suffix array (QUASAR). In Proceedings of the Third Annual International Conference on Research in Computational Molecular Biology (RECOMB), ACM, New York, pp. 77-83.
2. Hazelhurst, S. (2008) Algorithms for clustering EST sequences: the wcd tool. South African Comput. J., 24, 1542-1546.
3. Hazelhurst, S. and Bergheim, A. (2003) ESTsim: a tool for creating benchmarks for EST clustering algorithms. Technical Report TR-Wits-CS-2003-1. School of Computer Science, University of the Witwatersrand, Johannesburg, S.A.
4. Hazelhurst, S. et al. (2008) An overview of the wcd EST clustering tool. Bioinformatics, 24, 1542-1546.
5. Homann, R. et al. (2009) mkESA: enhanced suffix array construction tool. Bioinformatics, 25, 1084-1085.
6. Huang, X. and Madan, A. (1999) CAP3: a DNA sequence assembly program. Genome Res., 9, 868-877.
7. Jain, A.K. et al. (1999) Data clustering: a review. ACM Comput. Surv., 31, 264-323.
8. Kalyanaraman, A. et al. (2002) Parallel EST clustering. In Proceedings of IEEE Conference High Performance Computational Biology. IEEE Computer Society.
9. Levenshtein, V. (1966) Binary codes capable of correcting deletions, insertions, and reversals. Soviet Phys. Doklady, 10, 707-710.
10. Malde, K. et al. (2003) Fast sequence clustering using a suffix array algorithm. Bioinformatics, 19, 1221-1226.
11. Manber, U. and Myers, E.W. (1993) Suffix arrays: a new method for on-line string searches. SIAM J. Comput., 22, 935-948.
12. Manzini, G. and Ferragina, P. (2004) Engineering a lightweight suffix array construction algorithm. Algorithmica, 40, 33-50.
13. Miller, R. et al. (1999)Acomprehensive approach to clustering of expressed human gene sequence: the sequence tag alignment and consensus knowledge base. Genome Res., 9, 1143-1155.
14. Pertea, G. et al. (2003) TIGR gene indices clustering tools (TGICL): a software system for fast clustering of large EST datasets. Bioinformatics, 19, 651-652.
15. Picardi, E. et al. (2009) EasyCluster: a fast and efficient gene-oriented clustering tool for large-scale transcriptome data. BMC Bioinformatics, 10 (Suppl. 6), S10.
16. Pop, M. and Salzberg, S. (2008) Bioinformatics challenges of new sequencing technology. Trends Genetics, 24, 142-149.
17. Puglisi, S.J. et al. (2007) A taxonomy of suffix array construction algorithms. ACM Comput. Surv., 39, 1-31.
18. Rahmann, S. and Rivals, E. (2000) Exact and efficient computation of the expected number of missing and common words in random texts. In Proceedings of the 11th Annual Symposium Combinatorial Pattern Matching (CPM 2000), Vol. 1848 of Lecture Notes in Computer Science, Springer, pp. 375-387.
19. Rao, D. et al. (2010) PEACE: parallel environment for assembly and clustering of gene expression. Nucleic Acids Res., 38, W737-W742.
20. Reinert, G. et al. (2009) Alignment-free sequence comparison (I): Statistics and power. J. Comput. Biol., 16, 1615-1634.
21. Richter, D. et al. (2008) MetaSim - a sequencing simulator for genomics and metagenomics. PLoS One, 3, e3373.
22. Robison, K. (2010) Editorial: next generation sequencing. Brief. Bioinformatics, 11, 455-456.
23. Schwartz, D.C. andWaterman, M.S. (2009) New generations: Sequencing machines and their computational challenges. J. Comput. Sci. Technol., 25, 3-9.
24. Slater, G. (2000) Algorithms for the Analysis of Expressed Sequence Tags. PhD Thesis, University of Cambridge, Cambridge, UK.
25. Torney, D. et al. (1990) Computation of d2: a measure of sequence dissimilarity. In Bell, G. and Marr, T. (eds) Computers and DNA. Addison-Wesley, Boston, Mass, pp. 109-125.
26. Ukkonen, E. (1992) Approximate string-matching with q-grams and maximal matches. Theor. Comput. Sci., 92, 191-211.
27. Zimmermann, J. et al. (2004) Amethod for evaluating the quality of string dissimilarity measures and clustering algorithms for EST clustering. In Proceedings of the 4th IEEE International Symposium BioInformatics and BioEngineering (BIBE 2004). IEEE Computer Society, pp. 301-309.