Evolutionary sequence modeling for discovery of peptide hormones

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn 1, Issue , 2007, Pages

  Sönmez, Kemal ^a   Toll, Lawrence ^a   Zaveri, Nina ^a  

^a SRI INTERNATIONAL   (United States)

Author keywords

Evolutionary HMM; Hierarchical grammar; Peptide hormone

Indexed keywords

EVOLUTIONARY HMM; HIERARCHICAL GRAMMAR; PEPTIDE HORMONE;

COMPUTATIONAL METHODS; HIERARCHICAL SYSTEMS; HORMONES; PEPTIDES;

EVOLUTIONARY ALGORITHMS;

EID: 34547518271     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2007.366695     Document Type: Conference Paper

References (18)

1. Gibbs, R.A., et al., Genome sequence of the Brown Norway rat yields insights into mammalian evolution. Nature, 2004. 428(6982): p. 493-521.
2. Venter, J.C., et al., The sequence of the human genome. Science, 2001. 291(5507): p. 1304-51.
3. Siepel, A. and D. Haussler, Combining phylogenetic and hidden Markov models in biosequence analysis. J Comput Biol, 2004. 11(2-3): p. 413-28.
4. Bryant, C.H., Muggleton, S.H., Srinivasan, A., Whittaker, A., Topp, S., Rawlings, C., Are grammatical representations useful for learning from biological sequence data? - a case study. Linkoping Electronic Articles in Computer and Information Science, 2001. 6(2001)(13).
5. Felsenstein, J., Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol, 1981. 17(6): p. 368-76.
6. Yang, Z., A space-time process model for the evolution of DNA sequences. Genetics, 1995. 139(2): p. 993-1005.
7. Goldman, N., J.L. Thome, and D.T. Jones, Using evolutionary trees in protein secondary structure prediction and other comparative sequence analyses. J Mol Biol, 1996. 263(2): p. 196-208.
8. Thorne, J.L., N. Goldman, and D.T. Jones, Combining protein evolution and secondary structure. Mol Biol Evol, 1996. 13(5): p. 666-73.
9. Waterston, R.H., et al., Initial sequencing and comparative analysis of the mouse genome. Nature, 2002. 420(6915): p. 520-62.
10. Boffelli, D., et al., Phylogenetic shadowing of primate sequences o find functional regions of the human genome. Science, 2003. 299(5611): p. 1391-4.
11. Kellis, M., et al., Sequencing and comparison of yeast species to identify genes and regulatory elements. Nature, 2003. 423(6937): p. 241-54.
12. Thomas, J.W., et al., Comparative analyses of multi-species sequences from targeted genomic regions. Nature, 2003. 424(6950): p. 788-93.
13. Pedersen, J.S. and J. Hein, Gene finding with a hidden Markov model of genome structure and evolution. Bioinformatics, 2003. 19(2): p. 219-27.
14. McAuliffe, J.D., L. Pachter, and M.I. Jordan, Multiple-sequence functional annotation and the generalized hidden Markov phylogeny. Bioinformatics, 2004. 20(12): p. 1850-60.
15. Holmes, I., Using guide trees to construct multiple-sequence evolutionary HMMs. Bioinformatics, 2003. 19 Suppl 1: p. i147-57.
16. Holmes, I. and W.J. Bruno, Evolutionary HMMs: a Bayesian approach to multiple alignment. Bioinformatics, 2001.17(9): p. 803-20.
17. Sonmez, K. and L. Toll. A Novel Hidden Markov Model for Cross-Genome Discovery of Peptide Hormones. in GENSIPS 2005. 2005. Newport, RI, USA.
18. Felsenstein, J., Maximum-likelihood estimation of evolutionary trees from continuous characters. Am J Hum Genet, 1973. 25(5): p. 471-92.