Skip to main content
SpringerLink
Log in
Book cover

Statistical Methods in Molecular Evolution pp 407–438Cite as

Estimating Substitution Matrices

  • Chapter

  • 3528 Accesses

Part of the book series: Statistics for Biology and Health ((SBH))

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   139.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. S. F. Altschul. Amino acid substitution matrices from an information theoretic perspective. J. Mol. Biol., 219:555–565, 1991.

    Article  Google Scholar 

  2. L. Arvestad and W. J. Bruno. Estimation of reversible substitution matrices from multiple pairs of sequences. J. Mol. Evol., 45:696–703, 1997.

    Google Scholar 

  3. S. A. Benner, M. A. Cohen, and G. H. Gonnet. Amino acid substitution during functionally constrained divergent evolution of protein sequences. Protein Eng., 7:1323–1332, 1994.

    Google Scholar 

  4. P. Billingsley. Statistical Inference for Markov Processes. University of Chicago Press, Chicago, 1961.

    Google Scholar 

  5. S. E. Brenner, C. Chothia, and T. J. P. Hubbard. Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships. Proc. Natl. Acad. Sci. USA, 95:6073–6078, 1998.

    Article  Google Scholar 

  6. F. Chiaromonte, Yap V. B., and W. Miller. Scoring pairwise genomic sequence alignments. In R. B. Altman, A. K. Dunker, L. Hunter, K. Lauderdale, and T. E. Klein, editors, Proceedings of the Pacific Symposium on Biocomputing, pages 115–126. World Scientific, Singapore, 2002.

    Google Scholar 

  7. M. O. Dayhoff and R. V. Eck. A model of evolutionary change in proteins. In M. O. Dayhoff, editor, Atlas of Protein Sequence and Structure. National Biomedical Research Foundation, Silver Spring, MD, 1968.

    Google Scholar 

  8. M. O. Dayhoff, R. V. Eck, and C. M. Park. A model of evolutionary change in proteins. In M. O. Dayhoff, editor, Atlas of Protein Sequence and Structure, volume 5. National Biomedical Research Foundation, Washington, DC, 1972.

    Google Scholar 

  9. M. O. Dayhoff, R. M. Schwartz, and B. C. Orcutt. A model of evolutionary change in proteins. In M. O. Dayhoff, editor, Atlas of Protein Sequence and Structure, volume 5. National Biomedical Research Foundation, Washington, DC, 1979.

    Google Scholar 

  10. A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the EM algorithm. J. Roy. Stat. Soc. B, 39:1–38, 1977.

    MathSciNet  Google Scholar 

  11. C. Devauchelle, A. Grossmann, A. Hénaut, M. Holschneider, M. Monnerot, J. L. Risler, and B. Torrésani. Rate matrices for analyzing large families of protein sequences. J. Comput. Biol., 8:381–399, 2001.

    Article  Google Scholar 

  12. R. Durbin, S. Eddy, A. Krogh, and G. Mitchison. Biological Sequence Analysis. Cambridge University Press, Cambridge, 1998.

    Google Scholar 

  13. J. Felsenstein. Cases in which parsimony or compatibility methods will be positively misleading. Syst. Zool., 27:401–410, 1978.

    Google Scholar 

  14. J. Felsenstein. Evolutionary trees from DNA sequences. J. Mol. Evol., 18:368–376, 1981.

    Google Scholar 

  15. J. Felsenstein. Inferring Phylogenies. Sinauer Associates, Inc., Sunderland, MA, 2004.

    Google Scholar 

  16. D. F. Feng, M. S. Johnson, and R. F. Doolittle. Aligning amino acid sequences: Comparison of commonly used methods. J. Mol. Evol., 21:112–125, 1985.

    Article  Google Scholar 

  17. J. B. Fraleigh and R. A. Beauregard. Linear Algebra. Addison-Wesley, Reading, MA, 3rd edition, 1994.

    Google Scholar 

  18. M. P. Francino and H. Ochman. Strand asymmetries in DNA evolution. Trends Genet., 13:240–245, 1997.

    Article  Google Scholar 

  19. M. P. Francino and H. Ochman. Strand symmetry around the β-globin origin of replication in primates. Mol. Biol. Evol., 17:416–422, 2000.

    Google Scholar 

  20. M. Fukushima. Dirichlet Forms and Markov Processes. North Holland, Amsterdam, 1980.

    Google Scholar 

  21. R. D. Gill and S. Johansen. A survey of product-integration with a view towards application in survival analysis. Ann. Stat., 18:1501–1555, 1990.

    MathSciNet  Google Scholar 

  22. G. H. Gonnet, M. A. Cohen, and S. A. Benner. Exhaustive matching of the entire protein sequence database. Science, 256:1433–1445, 1992.

    Google Scholar 

  23. R. E. Green and S. E. Brenner. Bootstrapping and normalization for enhanced evaluations of pairwise sequence comparison. Proc. IEEE, 9:1837–1847, 2002.

    Google Scholar 

  24. S. Henikoff and J. G. Henikoff. Amino acid substitution matrices from protein blocks. Proc. Natl. Acad. Sci. USA, 89:10915–10919, 1992.

    Google Scholar 

  25. I. Holmes and G. M. Rubin. An expectation maximization algorithm for training hidden substitution models. J. Mol. Biol., 317:753–764, 2002.

    Article  Google Scholar 

  26. M. S. Johnson and J. P. Overington. A structural basis for sequence comparisons. J. Mol. Biol., 233:716–738, 1993.

    Article  Google Scholar 

  27. D. T. Jones, W. R. Taylor, and J. M. Thornton. The rapid generation of mutation data matrices from protein sequences. Comput. Appl. Biosci., 8:275–282, 1992.

    Google Scholar 

  28. F. P. Kelly. Reversibility and Stochastic Networks. John Wiley & Sons, New York, 1979.

    Google Scholar 

  29. J. M. Koshi and R. A. Goldstein. Context-dependent optimal substitution matrices. Protein Eng., 8:641–645, 1994.

    Google Scholar 

  30. P. Lió and N. Goldman. Models of molecular evolution and phylogeny. Genome Res., 8:1233–1244, 1998.

    Google Scholar 

  31. A. D. McLachlan. Tests for comparing related amino acid sequences. J. Mol. Biol., 61:409–424, 2002.

    Google Scholar 

  32. T. Müller, S. Rahmann, and M. Rehmsmeier. Non-symmetric score matrices and the detection of homologous transmembrane proteins. J. Mol. Evol., 17:182–189, 2001.

    Google Scholar 

  33. T Müller, R. Spang, and M. Vingron. Estimating amino acid substitution models: A comparison of Dayhoff’s estimator, the resolvent approach and a maximum likelihood method. Mol. Biol. Evol., 19:8–13, 2002.

    Google Scholar 

  34. T Müller and M. Vingron. Modeling amino acid replacement. J. Comput. Biol., 7:761–776, 2000.

    Google Scholar 

  35. S. Veerassamy, A. Smith, and E. R. M. Tillier. A transition probability model for amino acid substitutions from blocks. J. Comput. Biol., 10:997–1010, 2003.

    Article  Google Scholar 

  36. G. Vogt, T. Etzold, and P. Argos. An assessment of amino acid exchange matrices in aligning protein sequences: The twilight zone revisited. J. Mol. Biol., 249:816–831, 1995.

    Article  Google Scholar 

  37. W. J. Wilbur. On the PAM matrix model of protein evolution. Mol. Biol. Evol., 2:434–447, 1985.

    Google Scholar 

  38. V. B. Yap and T. P. Speed. Modeling DNA base substitution in large genomic regions from two organisms. J. Mol. Evol., 58:12–18, 2004.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mathematics, University of California, Berkley, CA, 94720-3840, USA

    Von Bing Yap

  2. Department of Statistics, University of California, Berkley, CA, 94720-3840, USA

    Terry Speed

Authors
  1. Von Bing Yap
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Terry Speed
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer Science+Business Media, Inc.

About this chapter

Cite this chapter

Yap, V.B., Speed, T. (2005). Estimating Substitution Matrices. In: Statistical Methods in Molecular Evolution. Statistics for Biology and Health. Springer, New York, NY. https://doi.org/10.1007/0-387-27733-1_15

Download citation

Publish with us

Policies and ethics

Search

Navigation