A hidden Markov model for progressive multiple alignment

Bioinformatics

Volumn 19, Issue 12, 2003, Pages 1505-1513

  Löytynoja, Ari ^a   Milinkovitch, Michel C ^a  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID SEQUENCE; ARTICLE; CORRELATION ANALYSIS; EVOLUTION; GENETIC ALGORITHM; NUCLEOTIDE SEQUENCE; PRIORITY JOURNAL; PROBABILITY; RELIABILITY; SEQUENCE ALIGNMENT;

EID: 0041886963     PISSN: 13674803     EISSN: None     Source Type: Journal    
DOI: 10.1093/bioinformatics/btg193     Document Type: Article

References (23)

1. Churchill,G.A. (1989) Stochastic models for heterogeneous DNA sequences. Bull. Math. Biol., 51, 79-94.
2. Durbin,R., Eddy,S., Krogh,A. and Mitchison,G. (1998) Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press, Cambridge.
3. Eddy,S.R. (1995) Multiple alignment using hidden Markov models. Proc. Int. Conf. Intell. Syst. Mol. Biol., 3, 114-120.
4. Feng,D.F. and Doolittle,R.F. (1987) Progressive sequence alignment as a prerequisite to correct phylogenetic trees. J. Mol. Evol., 25, 351-360.
5. Goldman,N., Thorne,J.L. and Jones,D.T. (1996) Using evolutionary trees in protein secondary structure prediction and other comparative sequence analyses. J. Mol. Biol., 263, 196-208.
6. Gotoh,O. (1982) An improved algorithm for matching biological sequences. J. Mol. Biol., 162, 705-708.
7. Hein,J., Wiuf,C., Knudsen,B., Moller,M.B. and Wibling,G. (2000) Statistical alignment: computational properties, homology testing and goodness-of-fit. J. Mol. Biol., 302, 265-279.
8. Holmes,I. and Bruno,W.J. (2001) Evolutionary hmms: a Bayesian approach to multiple alignment. Bioinformatics, 17, 803-820.
9. Ihaka,R. and Gentleman,R. (1996) R: a language for data analysis and graphics. J. Comput. Graph. Stat., 5, 299-314.
10. Jukes,T.H. and Cantor,C. (1969) Mammalian Protein Metabolism. Academic Press, New York, pp. 121-132.
11. Karplus,K., Barrett,C. and Hughey,R. (1998) Hidden Markov models for detecting remote protein homologies. Bioinformatics, 14, 846-856.
12. Loytynoja,A. and Milinkovitch,M.C. (2001) SOAP, cleaning multiple alignments from unstable blocks. Bioinformatics, 17, 573-574.
13. Needleman,S.B. and Wunsch.C.D. (1970) A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol., 48, 443-553.
14. Rabiner.L.R. (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE, 77, 257-286.
15. Saitou.N. and Nei,M. (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol., 4, 406-425.
16. Stoye,J., Evers,D. and Meyer,F. (1998) Rose: generating sequence families. Bioinformatics, 14, 157-163.
17. Thompson,J.D., Higgins,D.G. and Gibson,T.J. (1994) CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res., 22, 4673-4680.
18. Thompson,J.D, Plewniak,F. and Poch,O. (1999) BAliBASE: a benchmark alignment database for the evaluation of multiple alignment programs. Bioinformatics, 15, 87-88.
19. Thorne,J.L., Kishino,H. and Felsenstein,J. (1991) An evolutionary model for maximum likelihood alignment of DNA sequences. J. Mol. Evol., 33, 114-124.
20. Thorne,J.L., Kishino,H. and Felsenstein,J. (1992) Inching toward reality: an improved likelihood model of sequence evolution. J. Mol. Evol., 34, 3-16.
21. Vingron,M. (1996) Near-optimal sequence alignment. Curr. Opin. Struct. Biol., 6, 346-352.
22. Viterbi,A.J. (1967) Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Trans. Informat. Theor, IT-13, 260-269.
23. Whelan,S. and Goldman,N. (2001) A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach. Mol. Biol. Evol., 18, 691-699.