Finding exact optimal motifs in matrix representation by partitioning

Bioinformatics

Volumn 21, Issue SUPPL. 2, 2005, Pages

  Leung, Henry C M ^a   Chin, Francis Y L ^a  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; BIOINFORMATICS; GENE EXPRESSION REGULATION; GENE STRUCTURE; GENETIC ALGORITHM; PHASE PARTITIONING; PRIORITY JOURNAL; PROBABILITY; PROMOTER REGION; PROTEIN ANALYSIS; PROTEIN EXPRESSION; PROTEIN MOTIF;

EID: 27544437350     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/bti1115     Document Type: Article

References (25)

1. Bailey,T. and Elkan,C. (1995) Unsupervised learning of multiple motifs in biopolymers using expectation maximization. Mach. Learning, 21, 51-80.
2. Barash,Y., Bejerano,G. and Friedman,N. (2001) A simple hyper-geometric approach for discovering putative transcription factor binding sites. In Proceedings of the 1st Workshop on Algorithms in Bioinformatics (WABI 2001), BRICS, University of Aarhus, Denmark, pp. 278-293.
3. Brazma,A. et al. (1998) Approaches to the automatic discovery of patterns in biosequences. J. Comput. Biol., 5, 279-305.
4. Buhler,J. and Tompa,M. (2001) Finding motifs using random projections. In Proceedings of the fifth Annual International Conference on Computational Molecular Biology (RECOMB01), Montreal, Canada, pp. 69-76.
5. Chin,F and Leung,H. (2005) Voting Algorithms for Discovering Long Motifs. In Proceedings of the 3rd Asia-Pacific Bioinformatics Conference, (APBC 2005), Singapore, Imperial college press, London, pp. 261-271.
6. Chin,F., Leung,H., Yau,S.M., Lam,T.W., Rosenfeld,R., Tsang,W.W., Smith,D. and Jiang,Y. (2004) Finding motifs for insufficient number of sequences with strong binding to transcription factor. In Proceedings of the 8th Annual International Conference on Computational Molecular Biology, (RECOMB04), San Diego, CA, ACM Press, pp. 125-132.
7. Eskin,E. (2004a) From profiles to patterns and back again: A branch and bound algorithm for finding near optimal motif profiles. In Proceedings of the 8th Annual International Conference on Computational Molecular Biology, (RECOMB04), San Diego, CA, ACM Press, pp. 115-124.
8. Eskin,E. (2004b) Personal communication.
9. Lawrence,C. et al. (1993) Detecting subtule sequence signals: A Gibbs sampling strategy for multiple alignment. Science, 262, 208-214.
10. Lawrence,C. and Reilly,A. (1990) An expectation maximization (em) algorithm for the identification and characterization of common sites in unaligned biopolymer sequences. Proteins: Structure, Function and Genetics, 7, 41-51.
11. Leung,H. et al. (2005) Finding motifs with insufficient number of strong binding sites. J. Comput. Biol., in press.
12. Leung,H. and Chin,F. (2005) Generalized planted (l,d)-motif problem with negative set. In Proceedings of the 5th Workshop on Algorithms and Bioinformatics, (WABI 2005), Mallorca, Spain, in press.
13. Li,M. et al. (2002) Finding similar regions in many strings. J. Comput. Sys. Sci., 65, 73-96.
14. Liang,S. (2003) cWINNOWER Algorithm for Finding Fuzzy DNA Motifs. In Proceedings of the IEEE Computer Society Bioinformatics Conference (CSB 2003), Stanford university, CA, pp. 260-265.
15. Liu,J.S. et al. (1995) Bayesian motifs for multiple local sequence alignment and Gibbs sampling strategies. J. Am. Stat. Assoc., 432, 1156-1170.
16. Pevzner,P. and Sze,S.H. (2000) Combinatorial approaches to finding subtle signals in dna sequences. In Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology, (ISMB 2000), San Diego, CA, pp. 269-278.
17. Rocke,E. and Tompa,M. (1998) An algorithm for finding novel gapped motifs in DNA sequences. In Proceedings of the 2nd Annual International Conference on Computational Molecular Biology, (RECOMB98), Newyork, NY, pp. 228-233.
18. Sagot,M.F. (1998) Spelling approximate repeated or common motifs using a suffix tree. In Lucchesi,C.L. and Moura,A.V. (eds), Latin '98: Theoretical Informatics, Vol. 1380 of Lecture Notes in Computer Science, pp. 111-127.
19. Shinozaki,D. et al. (2003) Finding optimal degenerate patterns in DNA sequences. Bioinformatics, 19(Suppl 2), ii206-ii214.
20. Sinha,S. and Tompa,M. (2000) A statistical method for finding transcription factor binding sites. In Proceedings of the 8th International Conference on Intelligent Systems for Molecular Biology, (ISMB 2000), San Diego, CA, pp. 344-354.
21. Sinha,S. and Tompa,M. (2002) Discovery of novel transcription factor binding sites by statistical overrepresentation. Nucleic Acids Res., 30, 5549-5560.
22. Staden,R. (1989) Methods for discovering novel motifs in nucleic acid sequences. Comput. Appl. Biosci., 5, 293-298.
23. Tompa,M. (1999) An exact method for finding short motifs in sequences with application to the ribosome, binding site problem. In Proceedings of the 7th International Conference on Intelligent Systems for Molecular Biology, (ISMB 1999), Heidelberg, Germany, pp. 262-271.
24. Wolfertsteeter,F. et al. (1996) Identification of functional elements in unaligned nucleic acid sequences by a novel tuple search algorithm. Comput. Appl. Biosci., 12, 71-80.
25. Zhu,J. and Zhang,M. (1999) SCPD: A promoter database of the yeast Saccharomyces cerevisiae. Bioinformatics, 15, 563-577.