Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-qxdb6 Total loading time: 0 Render date: 2024-04-28T09:10:00.867Z Has data issue: false hasContentIssue false

References

Published online by Cambridge University Press:  05 June 2012

Philippe Lemey
Affiliation:
University of Oxford
Marco Salemi
Affiliation:
University of California, Irvine
Anne-Mieke Vandamme
Affiliation:
Katholieke Universiteit Leuven, Belgium
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
The Phylogenetic Handbook
A Practical Approach to Phylogenetic Analysis and Hypothesis Testing
, pp. 672 - 708
Publisher: Cambridge University Press
Print publication year: 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abascal, F., Posada, D., & Zardoya, R. (2007). MtArt: a new model of amino acid replacement for Arthropoda. Molecular Biology and Evolution, 24(1), 1–5.CrossRefGoogle ScholarPubMed
Abascal, F., Zardoya, R., & Posada, D. (2005). ProtTest: selection of best-fit models of protein evolution. Bioinformatics, 21(9), 2104–2105.CrossRefGoogle ScholarPubMed
Abdo, Z., Minin, V. N., Joyce, P., & Sullivan, J. (2005). Accounting for uncertainty in the tree topology has little effect on the decision-theoretic approach to model selection in phylogeny estimation. Molecular Biology and Evolution, 22(3), 691–703.CrossRefGoogle ScholarPubMed
Abecasis, A. B., Lemey, P., Vidal, N.et al. (2007). Recombination is confounding the early evolutionary history of HIV-1: subtype G is a circulating recombinant form. Journal of Virology, 81, 8543–8551.CrossRefGoogle Scholar
Adachi, J. & Hasegawa, M. (1996). Model of amino acid substitution in proteins encoded by mitochondrial DNA. Journal of Molecular Evolution, 42, 459–468.CrossRefGoogle ScholarPubMed
Adachi, J. & Hasegawa, M. (1996a). MOLPHY version 2.3: programs for molecular phylogenetics based on maximum likelihood. Computer Science Monographs of Institute of Statistical Mathematics, 28, 1–150.Google Scholar
Adachi, J. & Hasegawa, M. (1996b). Model of amino acid substitution in proteins encoded by mitochondrial DNA. Journal of Molecular Evolution, 42(4), 459–468.CrossRefGoogle ScholarPubMed
Adachi, J., Waddell, P. J., Martin, W., & Hasegawa, M. (2000). Plastid genome phylogeny and a model of amino acid substitution for proteins encoded by chloroplast DNA. Journal of Molecular Evolution, 50(4), 348–358.CrossRefGoogle Scholar
Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723.CrossRefGoogle Scholar
Aldous, D. J. (2001). Stochastic models and descriptive statistics for phylogenetic trees, from Yule to today. Statistical Science, 16, 23–34.CrossRefGoogle Scholar
Allison, A. C. (1956). Sickle cells and evolution. Scientific American, 87–94.CrossRefGoogle Scholar
Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment search tool. Journal of Molecular Biology, 215, 403–410.CrossRefGoogle ScholarPubMed
Altschul, S. F., Madden, T. L., Schäffer, A. A.et al. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research, 25, 3389–3402.CrossRefGoogle ScholarPubMed
Anderson, T. J., Haubold, B., Williams, J. T.et al. (2000). Microsatellite markers reveal a spectrum of population structures in the malaria parasite Plasmodium falciparum. Molecular Biology and Evolution, 17, 1467–1482.CrossRefGoogle ScholarPubMed
Andolfatto, P. (2005). Adaptive evolution of non-coding DNA in Drosophila. Nature, 437(7062), 1149–1152.CrossRefGoogle ScholarPubMed
Anisimova, M., Nielsen, R., & Yang, Z. (2003). Effect of recombination on the accuracy of the likelihood method for detecting positive selection at amino acid sites. Genetics, 164, 1229–1236.Google ScholarPubMed
Archibald, J. M. & Rogers, A. J. (2002). Gene conversion and the evolution of euryarchaeal chaperonins: a maximum likelihood-based method for detecting conflicting phylogenetic signals. Journal of Molecular Evolution, 55, 232–245.CrossRefGoogle ScholarPubMed
Archie, J. W. (1989). A randomization test for phylogenetic information in systematic data. Systematic Zoology, 38, 219–252.CrossRefGoogle Scholar
Aris-Brosou, S. & Yang, Z. (2003). Bayesian models of episodic evolution support a late Precambrian explosive diversification of the Metazoa. Molecular Biology and Evolution, 20(12), 1947–1954.CrossRefGoogle ScholarPubMed
Armougom, F., Moretti, S., Poirot, O.et al. (2006). Expresso: automatic incorporation of structural information in multiple sequence alignments using 3D-Coffee. Nucleic Acids Research, 34(Web Server issue), W604–W608.CrossRefGoogle ScholarPubMed
Awadalla, P. (2003). The evolutionary genomics of pathogen recombination. National Review in Geneties, 4, 50–60.CrossRefGoogle ScholarPubMed
Baake, E. (1998). What can and what cannot be inferred from pairwise sequence comparison?Mathematical Biosciences, 154, 1–21.CrossRefGoogle Scholar
Bäck, T. & Schwefel, H.-P. (1993). An overview of evolutionary algorithms for parameter optimization. Evolutionary Computation, 1, 1–23.CrossRefGoogle Scholar
Bailey, N. T. J. (1964). The Elements of Stochastic Processes with Application to the Natural Sciences. New York: Wiley.Google Scholar
Bakker, E. G., Stahl, E. A., Toomajian, C., Nordborg, M., Kreitman, M., & Bergelson, J. (2006). Distribution of genetic variation within and among local populations of Arabidopsis thaliana over its species range. Molecular Ecology, 15(5), 1405–1418.CrossRefGoogle ScholarPubMed
Baldauf, S. L., Palmer, J. D., & Doolittle, W. F. (1996). The root of the universal tree and the origin of eukaryotes based on elongation factor phylogeny. Proceedings of the National Academy of Sciences, USA, 93, 7749–7754.CrossRefGoogle ScholarPubMed
Bandelt, H.-J. (1995). Combination of data in phylogenetic analysis. Plant systematics and Evolution, 9, S355–S361.Google Scholar
Bandelt, H.-J. & Dress, A. (1992a). A canonical decomposition theory for metrics on a finite set. Advances in Mathematics, 92, 47–105.CrossRefGoogle Scholar
Bandelt, H.-J. & Dress, A. (1992b). Split decomposition: a new and useful approach to phylogenetic analysis of distance data. Molecular Phylogenetics and Evolution, 1, 242–252.CrossRefGoogle ScholarPubMed
Bandelt, H.-J. & Dress, A. (1993). A relational approach to split decomposition. In Information and Classification, ed. Opitz, O., Lausen, B., & Klar, R., pp. 123–131. Springer.CrossRefGoogle Scholar
Bandelt, H.-J., Forster, P., Sykes, B., & Richards, M. (1995). Mitochondrial portraits of human population using median networks. Genetics, 141, 743–753.Google Scholar
Barnes, I., Matheus, P., Shapiro, B., Jensen, D., & Cooper, A. (2002). Dynamics of Pleistocene population extinctions in Beringian brown bears. Science, 295(5563), 2267–2270.CrossRefGoogle ScholarPubMed
Barton, N. & Etheridge, A. M. (2004). The effect of selection on genealogies. Genetics, 166, 1115–1131.CrossRefGoogle ScholarPubMed
Bateman, A., Birney, E., Durbin, R., Eddy, S. R., Howe, K. L., & Sonnhammer, E. L. L. (2000). The Pfam protein families database. Nucleic Acids Research, 28, 263–266.CrossRefGoogle ScholarPubMed
Beaumont, M. A. (1999). Detecting population expansion and decline using microsatellites. Genetics, 153(4), 2013–2029.Google ScholarPubMed
Beerli, P. (2006). Comparison of Bayesian and maximum likelihood inference of population genetic parameters. Bioinformatics, 22, 341–345.CrossRefGoogle ScholarPubMed
Beerli, P. & Felsenstein, J. (1999). Maximum likelihood estimation of migration rates and effective population numbers in two populations using a coalescent approach. Genetics, 152, 763–773.Google ScholarPubMed
Benjamini, Y. & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal Royal Statistics Society B, 57(1), 289–300.Google Scholar
Bersaglieri, T., Sabeti, P. C., Patterson, N.et al. (2004). Genetic signatures of strong recent positive selection at the lactase gene. American Journal of Human Genetics, 74(6), 1111–1120.CrossRefGoogle ScholarPubMed
Bininda-Emonds, O. R. (2005). transAlign: using amino acids to facilitate the multiple alignment of protein-coding DNA sequences. BMC Bioinformatics, 6, 156.CrossRefGoogle ScholarPubMed
Birky, C. W. & Walsh, J. B. (1988). Effects of linkage on rates of molecular evolution. Proceedings of the National Academy of Sciences, USA, 85(17), 6414–6418.CrossRefGoogle ScholarPubMed
Birney, E., Thompson, J. D., & Gibson, T. J. (1996). PairWise and SearchWise: finding the optimal alignment in a simultaneous comparison of a protein profile against all DNA translation frames. Nucleic Acids Research, 24, 2730–2739.CrossRefGoogle Scholar
Bollback, J. P. (2002). Bayesian model adequacy and choice in phylogenetics. Molecular Biology and Evolution, 19(7), 1171–1180.CrossRefGoogle ScholarPubMed
Boni, M. F., Posada, D., & Feldman, M. W. (2007). An exact nonparametric method for inferring mosaic structure in sequence triplets. Genetics, 176, 1035–1047.CrossRefGoogle ScholarPubMed
Bray, N. & Pachter, L. (2004). MAVID: constrained ancestral alignment of multiple sequences. Genome Research, 14(4), 693–699.CrossRefGoogle ScholarPubMed
Bremer, K. (1988). The limits of amino-acid sequence data in angiosperm phylogenetic reconstruction. Evolution, 42, 795–803.CrossRefGoogle ScholarPubMed
Brenner, S. E., Chothia, C., & Hubbard, T. P. J. (1998). Assessing sequence comparison methods with reliable structurally identified distant evolutionary relationships. Proceedings of the National Academy of Sciences, USA, 95, 6073–6078.CrossRefGoogle ScholarPubMed
Britten, R. J. (1986). Rates of DNA sequence evolution differ between taxonomic groups. Science, 231, 1393–1398.CrossRefGoogle ScholarPubMed
Brocchieri, L. & Karlin, S. (1998). A symmetric-iterated multiple alignment of protein sequences. Journal of Molecular Biology, 276(1), 249–264.CrossRefGoogle ScholarPubMed
Brodie, R., Smith, A. J., Roper, R. L., Tcherepanov, V., & Upton, C. (2004). Base-By-Base: single nucleotide-level analysis of whole viral genome alignments. BMC Bioinformatics, 5, 96.CrossRefGoogle ScholarPubMed
Bromham, L. & Penny, D. (2003). The modern molecular clock. National Reviews in Genetics, 4(3), 216–224.CrossRefGoogle ScholarPubMed
Bromham, L., Penny, D., Rambaut, A., & Hendy, M. D. (2000). The power of relative rates tests depends on the data. Journal of Molecular Evolution, 50(3), 296–301.CrossRefGoogle ScholarPubMed
Brown, C. J., Garner, E. C., KeithDunker, A. Dunker, A., & Joyce, P. (2001). The power to detect recombination using the coalescent. Molecular Biology of Evolution, 18, 1421–1424.CrossRefGoogle ScholarPubMed
Brudno, M. & Morgenstern, B. (2002). Fast and sensitive alignment of large genomic sequences. Proceedings of the IEEE Computer Society Bioinformatics Conference, 1, 138–147.CrossRefGoogle ScholarPubMed
Brudno, M., Do, C. B., Cooper, G. M.et al. (2003). LAGAN and Multi-LAGAN: efficient tools for large-scale multiple alignment of genomic DNA. Genome Research, 13(4), 721–731.CrossRefGoogle ScholarPubMed
Bruen, T. C., Philippe, H., & Bryant, D. (2006). A simple and robust statistical test for detecting the presence of recombination. Genetics, 172, 2665–2681.CrossRefGoogle Scholar
Bruno, W. J., Socci, N. D., & Halpern, A. L. (2000). Weighted neighbor-joining: a likelihood-based approach to distance-based phylogeny reconstruction. Molecular Biology and Evolution, 17, 189–197.CrossRefGoogle ScholarPubMed
Bryant, D. & Moulton, V. (2004). NeighborNet: an agglomerative method for the construction of phylogenetic networks. Molecular Biology and Evolution, 21, 255–265.CrossRefGoogle Scholar
Buendia, P. & Narasimhan, G. (2007). Sliding MinPD: Building evolutionary networks of serial samples via an automated recombination detection approach. Bioinformatics, 23, 2993–3000.CrossRefGoogle ScholarPubMed
Buneman, P. (1971). The recovery of trees from measures of dissimilarity. In Mathematics in the Archeological and Historical Sciences, ed. Hodson, F. R., Kendall, D. G., & Tautu, P., pp. 387–395. Edinburgh, UK: Edinburgh University Press.Google Scholar
Burnham, K. P. & Anderson, D. R. (1998). Model Selection and Inference: A Practical Information-Theoretic Approach. New York, NY: Springer-Verlag.CrossRefGoogle Scholar
Burnham, K. P. & Anderson, D. R. (2003). Model Selection and Multimodel Inference: A Practical Information-theoretic Approach. New York, NY: Springer-Verlag.Google Scholar
Bush, R. M., Bender, C. A., Subbarao, K., Cox, N. J., & Fitch, W. M. (1999). Predicting the evolution of human Influenza A. Science, 286(5446), 1921–1925.CrossRefGoogle ScholarPubMed
Bustamante, C. D., Nielsen, R., & Hartl, D. L. (2002). A maximum likelihood method for analyzing pseudogene evolution: implications for silent site evolution in humans and rodents. Molecular Biology and Evolution, 19(1), 110–117.CrossRefGoogle ScholarPubMed
Bustamante, C. D., Nielsen, R., Sawyer, S. A., Olsen, K. M., Purugganan, M. D., & Hartl, D. L. (2002). The cost of inbreeding in Arabidopsis. Nature, 416(6880), 531–534.CrossRefGoogle ScholarPubMed
Bustamante, C. D., Fledel-Alon, A., Williamson, S.et al. (2005). Natural selection on protein-coding genes in the human genome. Nature, 437(7062), 1153–1157.CrossRefGoogle ScholarPubMed
Cao, Y., Adachi, J., & Hasegawa, M. (1998). Comments on the quartet puizlling method for finding maximum-likelihood tree topologies. Molecular Biology and Evolution, 15(1), 87–89.CrossRefGoogle Scholar
Cao, Y., Adachi, J., Janke, A., Paabo, S., & Hasegawa, M. (1994). Phylogenetic relationships among eutherian orders estimated from inferred sequences of mitochondrial proteins: instability of a tree based on a single gene. Journal of Molecular Evolution, 39, 519–527.CrossRefGoogle ScholarPubMed
Carroll, S. B. (1995). Homeotic genes and the evolution of arthropods and chordates. Nature, 376, 479–485.CrossRefGoogle ScholarPubMed
Carvajal-Rodriguez, A., Crandall, K. A., & Posada, D. (2006). Recombination estimation under complex evolutionary models with the coalescent composite-likelihood method. Molecular Biology and Evolution, 23, 817–827.CrossRefGoogle ScholarPubMed
Carvajal-Rodriguez, A., Crandall, K. A., & Posada, D. (2007). Recombination favors the evolution of drug resistance in HIV-1 during antiretroviral therapy. Infections and Genetic Evolution, 7, 476–483.CrossRefGoogle ScholarPubMed
Castillo-Davis, C. I., Bedford, T. B., & Hartl, D. L. (2004). Accelerated rates of intron gain/loss and protein evolution in duplicate genes in human and mouse malaria parasites. Molecular Biology and Evolution, 21(7), 1422–1427.CrossRefGoogle ScholarPubMed
Cavalli-Sforza, L. L. & Edwards, A. W. F. (1967). Phylogenetic analysis: Models and estimation procedures. Evolution, 32, 550–570.CrossRefGoogle Scholar
Chakrabarti, S., Lanczycki, C. J., Panchenko, A. R., Przytycka, T. M., Thiessen, P. A., & Bryant, S. H. (2006). Refining multiple sequence alignments with conserved core regions. Nucleic Acids Research, 34(9), 2598–2606.CrossRefGoogle ScholarPubMed
Chamary, J. V., Parmley, J. L., & Hurst, L. D. (2006). Hearing silence: non-neutral evolution at synonymous sites in mammals. National Reviews in Genetics, 7, 98–108.CrossRefGoogle ScholarPubMed
Chan, C. X., Beiko, R. G., & Ragan, M. A. (2006). Detecting recombination in evolving nucleotide sequences. BMC Bioinformatics, 7, 412.CrossRefGoogle ScholarPubMed
Chao, L., Tran, T. R., & Matthews, C. (1992). Muller's ratchet and the advantage of sex in the RNA virus ϕ6. Evolution, 46, 289–299.Google Scholar
Chao, L. & Tran, T. T. (1997). The advantage of sex in the RNA virus phi6. Genetics, 147, 953–959.Google ScholarPubMed
Chare, E. R. & Holmes, E. C. (2006). A phylogenetic survey of recombination frequency in plant RNA viruses. Archives of Virology, 151, 933–946.CrossRefGoogle ScholarPubMed
Chare, E. R., Gould, E. A., & Holmes, E. C. (2003). Phylogenetic analysis reveals a low rate of homologous recombination in negative-sense RNA viruses. Journal of General Virology, 84, 2691–2703.CrossRefGoogle ScholarPubMed
Charleston, M. A., Hendy, M. D., & Penny, D. (1994). The effect of sequence length, tree topology, and number of taxa on the performance of phylogenetic methods. Journal of Computational Biology, 1, 133–151.CrossRefGoogle Scholar
Chen, Y., Emerson, J. J., & Martin, T. M. (2005). Evolutionary genomics: codon volatility does not detect selection. Nature, 433(7023), E6–E7; discussion E7–E8.CrossRefGoogle Scholar
Cho, S., Mitchell, A., Regier, J. C.et al. (1995). A highly conserved nuclear gene for low-level phylogenetics: elongation factor-1a recovers morphology-based tree for heliothine moths. Molecular Biology and Evolution, 12, 650–656.Google Scholar
Clamp, M., Cuff, J., Searle, S. M., & Barton, G. J. (2004). The Jalview Java alignment editor. Bioinformatics, 20(3), 426–427.CrossRefGoogle ScholarPubMed
Comeron, J. M. & Guthrie, T. B. (2005). Intragenic Hill-Robertson interference influences selection intensity on synonymous mutations in Drosophila. Molecular Biology and Evolution, 22(12), 2519–2530.CrossRefGoogle ScholarPubMed
Corpet, F. (1988). Multiple sequence alignment with hierarchical clustering. Nucleic Acids Research, 16(22), 10881–10890.CrossRefGoogle ScholarPubMed
Cox, D. R. (1961). Tests of separate families of hypotheses. In Proceedings of the 4th Berkeley Symposium on Mathematical Statistics and Probability, pp. 105–123. Berkeley, CA, USA: UCB Press.Google Scholar
Cox, D. R. (1962). Further results on tests of separate families of hypotheses. Journal of the Royal Society of Statistics B, 24, 406–424.Google Scholar
Crill, W. D., Wichman, H. A., & Bull, J. J. (2000). Evolutionary reversals during viral adaptation to alternating hosts. Genetics, 154(1), 27–37.Google ScholarPubMed
Cuevas, J. M., Moya, A., & Elena, S. F. (2003). Evolution of RNA virus in spatially structured heterogeneous environments. Journal of Evolutionary Biology, 16(3), 456–466.CrossRefGoogle ScholarPubMed
Dagan, T. & Graur, D. (2005). The comparative method rules! Codon volatility cannot detect positive Darwinian selection using a single genome sequence. Molecular Biology and Evolution, 22(3), 496–500.CrossRefGoogle ScholarPubMed
Darwin, C. (1859). On the Origin of Species by Means of Natural Selection. London: Murray.Google Scholar
Dayhoff, M. O. (ed.) (1978). Atlas of Protein Sequence and Structure, vol. 5, Silver Spring, MD: National Biomedical Research Foundation.
Dayhoff, M. O., Schwartz, R. M., & Orcutt, B. C. (1978). A model of evolutionary change in proteins. In Atlas of Protein Sequence and Structure, vol. 5, suppl. 3, ed. Dayhoff, M. O., pp. 345–352. Washington DC, USA: National Biomedical Research Foundation.Google Scholar
Oliveira, T., Miller, R., Tarin, M., & Cassol, S. (2003). An integrated genetic data environment (GDE)-based LINUX interface for analysis of HIV-1 and other microbial sequences. Bioinformatics, 19(1), 153–154.CrossRefGoogle ScholarPubMed
Oliveira, T., Deforche, K., Cassol, S.et al. (2005). An automated genotyping system for analysis of HIV-1 and other microbial sequences. Bioinformatics, 21, 3797–3800.CrossRefGoogle ScholarPubMed
Oliveira, T., Pybus, O. G., Rambaut, A.et al. (2006). Molecular epidemiology: HIV-1 and HCV sequences from Libyan outbreak. Nature, 444(7121), 836–837.CrossRefGoogle ScholarPubMed
Queiroz, K. & Poe, S. (2001). Philosophy and phylogenetic inference: A comparison of likelihood and parsimony methods in the context of Karl Popper's writings on corroboration. Systematic Biology, 50, 305–321.CrossRefGoogle ScholarPubMed
DeBry, R. W. (2001). Improving interpretation of the decay index for DNA sequence data. Systematic Biology, 50, 742–752.CrossRefGoogle ScholarPubMed
Debyser, Z., Wijngaerden, E., Laethem, K.et al. (1998). Failure to quantify viral load with two of the three commercial methods in a pregnant woman harbouring an HIV-1 subtype G strain. AIDS Research and Human Retroviruses, 14, 453–459.CrossRefGoogle Scholar
Depiereux, E. & Feytmans, E. (1992). MATCH-BOX: a fundamentally new algorithm for the simultaneous alignment of several protein sequences. Computer Applications in the Biosciences, 8(5), 501–509.Google ScholarPubMed
Desai, M. M., Fisher, D. S., & Murray, A. W. (2007). The speed of evolution and maintenance of variation in asexual populations. Current Biology, 17(5), 385–394.CrossRefGoogle ScholarPubMed
Desper, R. & Gascuel, O. (2002). Fast and accurate phylogeny reconstruction algorithms based on the minimum-evolution principle. Journal of Computational Biology, 9, 687–705.CrossRefGoogle ScholarPubMed
Desper, R. & Gascuel, O. (2004). Theoretical foundation of the balanced minimum evolution method of phylogenetic inference and its relationship to weighted least-squares tree fitting. Molecular Biology and Evolution, 21, 587–598.CrossRefGoogle ScholarPubMed
Dimmic, M. W., Rest, J. S., Mindell, D. P., & Goldstein, R. A. (2002). rtREV: an amino acid substitution matrix for inference of retrovirus and reverse transcriptase phylogeny. Journal of Molecular Evolution, 55(1), 65–73.CrossRefGoogle ScholarPubMed
Do, C. B., Mahabhashyam, M. S., Brudno, M., & Batzoglou, S. (2005). ProbCons: probabilistic consistency-based multiple sequence alignment. Genome Research, 15(2), 330–340.CrossRefGoogle ScholarPubMed
Do, C. B., Woods, D. A., & Batzoglou, S. (2006). The Tenth Annual International Conference on Computational Molecular Biology, vol. 3909, CONTRAlign: discriminative training for protein sequence alignment. In Computational Molecular Biology, pp. 160–174. Berlin/Heidelberg: Springer.CrossRefGoogle Scholar
Domingo, E. (2006). Quasispecies: concept and implications for virology. Current Topics in Microbiology and Immunology, 299, 51–92.Google Scholar
Donoghue, M. J., Olmstead, R. G., Smith, J. F., & Palmer, J. D. (1992). Phylogenetic relationships of Dipsacales based on rbcL sequences. Annals of the Missouri Botanical Garden, 79, 333–345.CrossRefGoogle Scholar
Doolittle, R. F. (1987). Of URFs and ORFs. University Science Books.Google Scholar
Dopazo, J., Dress, A., & Haeseler, A. (1993). Split decomposition: A technique to analyze viral evolution. Proceedings of the National Academy of Sciences, USA, 90, 10320–10324.CrossRefGoogle ScholarPubMed
Dorit, R. L., Akashi, H., & Gilbert, W. (1995). Absence of polymorphism at the ZFY locus on the human Y chromosome. Science, 268, 1183–1185.CrossRefGoogle ScholarPubMed
Dress, A. & Krüger, M. (1987). Parsimonious phylogenetic trees in metric spaces and simulated annealing. Advances in Applied Mathematics, 8, 8–37.CrossRefGoogle Scholar
Dress, A. & Wetzel, R. (1993). The human organism – a place to thrive for the immuno-deficiency virus. In Proceedings of IFCS, Pairs.Google Scholar
Dress, A., Huson, D., & Moulton, V. (1996). Analyzing and visualizing sequence and distance data using SplitsTree. Discrete and Applied Mathematics, 71, 95–109.CrossRefGoogle Scholar
Dress, A., Hendy, M., Huber, K., & Moulton, V. (1997). On the number of vertices and branches in the Buneman graph. Annals in Combinatorics, 1, 329–337.CrossRefGoogle Scholar
Drouin, G., Prat, F., Ell, M., & Clarke, G. D. (1999). Detecting and characterizing gene conversions between multigene family members. Molecular Biology and Evolution, 16, 1369–1390.CrossRefGoogle ScholarPubMed
Drummond, A. & Strimmer, K. (2001). PAL: an object-oriented programming library for molecular evolution and phylogenetics. Bioinformatics, 17(7), 662–663.CrossRefGoogle ScholarPubMed
Drummond, A. J., Ho, S. Y. W., Phillips, M. J., & Rambaut, A. (2006). Relaxed phylogenetics and dating with confidence. PLoS Biology, 4(5).CrossRefGoogle Scholar
Drummond, A. J., Nicholls, G. K., Rodrigo, A. G., & Solomon, W. (2002). Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data. Genetics, 161(3), 1307–1320.Google ScholarPubMed
Drummond, A. J., Pybus, O. G., Rambaut, A., Forsberg, R., & Rodrigo, A. G. (2003). Measurably evolving populations. Trends in Ecology and Evolution, 18(9), 481–488.CrossRefGoogle Scholar
Drummond, A. J., Rambaut, A., Shapiro, B., & Pybus, O. G. (2005). Bayesian coalescent inference of past population dynamics from molecular sequences. Molecular Biology and Evolution, 22, 1185–1192.CrossRefGoogle ScholarPubMed
Durbin, R., Eddy, S., Krogh, A., & Mitchison, G. (1998). Biological Sequence Analysis. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Dutheil, J., Pupko, T., Alain, J.-M., & Galtier, N. (2005). A model-based approach for detecting coevolving positions in a molecule. Molecular Biology and Evolution, 22(9), 1919–1928.CrossRefGoogle ScholarPubMed
Edgar, R. C. & Batzoglou, S. (2006). Multiple sequence alignment. Current Opinions on Structural Biology, 16(3), 368–373.CrossRefGoogle ScholarPubMed
Edgar, R. C. & Sjolander, K. (2003). SATCHMO: sequence alignment and tree construction using hidden Markov models. Bioinformatics, 19(11), 1404–1411.CrossRefGoogle ScholarPubMed
Edgar, R. C. (2004a). MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics, 5, 113.CrossRefGoogle ScholarPubMed
Edgar, R. C. (2004b). MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research, 32(5), 1792–1797.CrossRefGoogle ScholarPubMed
Edwards, A. W. F. (1972). Likelihood. Cambridge, UK: Cambridge University Press.Google Scholar
Efron, B. (1979). Bootstrap methods: another look at the jackknife. Annals of Statistics, 7, 1–26.CrossRefGoogle Scholar
Efron, B. & Gong, G. (1983). A leisurely look at the bootstrap, the jackknife, and cross-validation. American Statistician, 37, 36–48.Google Scholar
Efron, B. & Tibshirani, R. (1994). An Introduction to the Bootstrap. New York: Chapman and Hall.Google Scholar
Efron, B., Halloran, E., & Holmes, S. (1996). Bootstrap confidence levels for phylogenetic trees. Proceedings of the National Academy of Sciences, USA, 93(23), 13429–13434.CrossRefGoogle ScholarPubMed
Eigen, M. & Biebricher, C. (1988). Sequence space and quasispecies distribution. In RNA Genetics, vol. 3, ed. Domingo, E., Holland, J. J., & Ahlquist, P., pp. 211–245. Boca Raton, Fl: CRC Press.Google Scholar
Endo, T., Ikeo, K., & Gojobori, T. (1996). Large-scale search for genes on which positive selection may operate. Molecular Biology and Evolution, 13(5), 685–690.CrossRefGoogle ScholarPubMed
Etherington, G. J., Dicks, J., & Roberts, I. N. (2005). Recombination Analysis Tool (RAT): a program for the high-throughput detection of recombination. Bioinformatics, 21, 278–281.CrossRefGoogle Scholar
Evans, J., Sheneman, L., & Foster, J. (2006). Relaxed neighbor joining: a fast distance-based phylogenetic tree construction method. Journal of Molecular Evolution, 62(6), 785–792.CrossRefGoogle ScholarPubMed
Evans, P. D., Mekel-Bobrov, N., Vallender, E. J., Hudson, R. R., & Lahn, B. T. (2006). Evidence that the adaptive allele of the brain size gene microcephalin introgressed into Homo sapiens from an archaic Homo lineage. Proceedings of the National Academy of Sciences, USA, 103(48), 18178–18183.CrossRefGoogle ScholarPubMed
Ewens, W. (1972). The sampling theory of selectively neutral alleles. Journal of Theoretical Biology, 3, 87–112.CrossRefGoogle ScholarPubMed
Eyre-Walker, A., Woolfit, M., & Phelps, T. (2006). The distribution of fitness effects of new deleterious amino acid mutations in humans. Genetics, 173(2), 891–900.CrossRefGoogle ScholarPubMed
Faith, D. P. (1991). Cladistic permutation tests for monophyly and nonmonophyly. Systematic Zoology, 40, 366–375.CrossRefGoogle Scholar
Fang, F., Ding, J., Minin, V. N., Suchard, M. A., & Dorman, K. S. (2007). cBrother: relaxing parental tree assumptions for Bayesian recombination detection. Bioinformatics, 23, 507–508.CrossRefGoogle ScholarPubMed
Farris, J. S. (1970). Estimating phylogenetic trees from distance matrixes. American Nature, 106, 645–668.CrossRefGoogle Scholar
Farris, J. S. (1977). On the phenetic approach to vertebrate classification. In Major Patterns in Vertebrate Evolution, ed. Hecht, M. K., Goody, P. C., & Hecht, B. M., pp. 823–850. New York: Plenum Press.CrossRefGoogle Scholar
Fay, J. C. & Wu, C. I. (2000). Hitchhiking under positive Darwinian selection. Genetics, 155(3), 1405–1413.Google ScholarPubMed
Fearnhead, P. & Donnelly, P. (2001). Estimating recombination rates from population genetic data. Genetics, 159, 1299–1318.Google ScholarPubMed
Felsenstein, J. (1974). The evolutionary advantage of recombination. Genetics, 78, 737–756.Google ScholarPubMed
Felsenstein, J. (1978a). Cases in which parsimony and compatibility methods will be positively misleading. Systematic Zoology, 27, 401–410.CrossRefGoogle Scholar
Felsenstein, J. (1978b). The number of evolutionary trees. Systematic Zoology, 27, 27–33.CrossRefGoogle Scholar
Felsenstein, J. (1981). Evolutionary trees from DNA sequences: a maximum likelihood approach. Journal of Molecular Evolution, 17, 368–376.CrossRefGoogle ScholarPubMed
Felsenstein, J. (1982). Numerical methods for inferring evolutionary trees. Quarterly Review of Biology, 57, 379–404.CrossRefGoogle Scholar
Felsenstein, J. (1984). Distance methods for inferring phylogenies: a justification. Evolution, 38, 16–24.CrossRefGoogle ScholarPubMed
Felsenstein, J. (1985). Confidence limits on phylogenies: an approach using the bootstrap. Evolution, 39, 783–791.CrossRefGoogle ScholarPubMed
Felsenstein, J. (1988). Phylogenies from molecular sequences: inference and reliability. Annual Review of Genetics, 22, 521–565.CrossRefGoogle ScholarPubMed
Felsenstein, J. (1989). Phylip – phylogeny inference package (version 3.2). Cladistics, 5, 164–166.Google Scholar
Felsenstein, J. (1993). PHYLIP (Phylogeny Inference Package) version 3.5c. Distributed by the author. Department of Genetics, University of Washington, Seattle.
Felsenstein, J. (1996). PHYLIP: Phylogeny Inference Package, Version 3.572c. Seattle, WA: University of Washington.Google Scholar
Felsenstein, J. (2004). Inferring Phylogenies. Sunderland, MA: Sinauer.Google Scholar
Felsenstein, J. (2006). Accuracy of coalescent likelihood estimates: do we need more sites, more sequences, or more loci? Molecular Biology and Evolution, 23, 691–700.CrossRefGoogle ScholarPubMed
Felsenstein, J. & Churchill, G. A. (1996). A Hidden Markov model approach to variation among sites in rate of evolution. Molecular Biology and Evolution, 13(1), 93–104.CrossRefGoogle ScholarPubMed
Felsenstein, J. & Kishino, H. (1993). Is there something wrong with the bootstrap on phylogenies? A reply to Hillis and Bull. Systematic Biology, 42, 193–200.CrossRefGoogle Scholar
Felsenstein, J., Kuhner, M. K., Yamato, J., & Beerli, P. (1999). Likelihoods on coalescents: a Monte Carlo sampling approach to inferring parameters from population samples of molecular data. In Statistics in Genetics and Molecular Biology, ed. Seillier-Moiseiwitsch, F., IMS Lecture Notes-Monograph Series, pp. 163–185.CrossRefGoogle Scholar
Feng, D. F. & Doolittle, R. F. (1987). Progressive sequence alignment as a prerequisite to correct phylogenetic trees. Journal of Molecular Evolution, 25(4), 351–360.CrossRefGoogle ScholarPubMed
Fernandes, A. P., Nelson, K., & Beverley, S. M. (1993). Evolution of nuclear ribosomal RNAs in kinetoplastid protozoa: perspectives on the age and origins of parasitism. Proceedings of the National Academy of Sciences, USA, 90, 11608–11612.CrossRefGoogle ScholarPubMed
Fisher, R. A. (1930). The Genetical Theory of Natural Selection. UK: Clarendon Press.CrossRefGoogle Scholar
Fisher, R. A. (1971). Design of Experiments. 9th edn., Macmillan.Google Scholar
Fitch, W. (1981). A non-sequential method for constructing trees and hierarchical classifications. Journal of Molecular Evolution, 18, 30–37.CrossRefGoogle ScholarPubMed
Fitch, W. M. (1971). Toward defining the course of evolution: minimum change for a specific tree topology. Systematic Zoology, 20, 406–416.CrossRefGoogle Scholar
Fitch, W. M. & Margoliash, E. (1967). Construction of phylogenetic trees: A method based on mutation distances as estimated from cytochrome c sequences is of general applicability. Science, 155, 279–284.CrossRefGoogle Scholar
Fitch, W. M. & Margoliash, E. (1967). Construction of phylogenetic trees. Science, 155, 279–284.CrossRefGoogle ScholarPubMed
Fleissner, R., Metzler, D., & Haeseler, A. (2005). Simultaneous statistical multiple alignment and phylogeny reconstruction. Systematic Biology, 54, 548–561.CrossRefGoogle ScholarPubMed
Friedlander, T. P., Horst, K. R., Regier, J. C., Mitter, C., Peigler, R. S., & Fez, Q. Q. (1998). Two nuclear genes yield concordant relationships within Attacini (Lepidoptera: Saturniidae)Molecular Phylogenetics and Evolution, 9, 131–140.CrossRefGoogle Scholar
Friedman, R. & Hughes, A. L. (2005). Codon volatility as an indicator of positive selection: data from eukaryotic genome comparisons. Molecular Biology and Evolution, 22(3), 542–546.CrossRefGoogle ScholarPubMed
Frost, S. D. W., Nijhuis, M., Schuurman, R., Boucher, C. A. B., & Leigh Brown, A. J. (2000). Evolution of lamivudine resistance in human immunodeficiency virus type 1-infected individuals: the relative roles of drift and selection. Journal of Virology, 74(14), 6262–6268.CrossRefGoogle Scholar
Frost, S. D. W., Liu, Y., Kosakovsky Pond, S. L.et al. (2005a). Characterization of human immunodeficiency virus type 1 (HIV-1) envelope variation and neutralizing antibody responses during transmission of HIV-1 subtype B. Journal of Virology, 79(10), 6523–6527.CrossRefGoogle ScholarPubMed
Frost, S. D. W., Wrin, T., Smith, D. M.et al. (2005b). Neutralizing antibody responses drive the evolution of human immunodeficiency virus type 1 envelope during recent HIV infection. Proceedings of the National Academy of Sciences, USA, 102(51), 18514–18519.CrossRefGoogle ScholarPubMed
Fu, Y. X. & Li, W. H. (1993). Statistical tests of neutrality of mutations. Genetics, 133(3), 693–709.Google ScholarPubMed
Galtier, N., Gouy, M., & Gautier, C. (1996). SeaView and Phylo_win, two graphic tools for sequence alignment and molecular phylogeny. Computer Applications in the Biosciences, 12, 543–548.Google ScholarPubMed
Gao, F., Robertson, D. L., Carruthers, C. D.et al. (1998). A comprehensive panel of near-full-length clones and reference sequences for non-subtype B isolates of human immunodeficiency virus type 1. Journal of Virology, 72, 5680–5698.Google ScholarPubMed
Gascuel, O. (1997). BIONJ: an improved version of the NJ algorithm based on a simple model of sequence data. Molecular Biology and Evolution, 14(7), 685–695.CrossRefGoogle ScholarPubMed
Gelman, A. & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical Science, 7(4), 457–511.CrossRefGoogle Scholar
Georgescu, M. M., Delpeyroux, F., Tardy-Panit, M.et al. (1994). High diversity of poliovirus strains isolated from the central nervous system from patients with vaccine-associated paralytic poliomyelitis. Journal of Virology, 68, 8089–8101.Google ScholarPubMed
Gerrish, P. J. & Lenski, R. E. (1998). The fate of competing beneficial mutations in an asexual population. Genetica, 103, 127–144.CrossRefGoogle Scholar
Geyer, C. J. (1991). Markov chain Monte Carlo maximum likelihood. In Computing Science and Statistics: Proceedings of the 23rd Symposium on the Interface, ed. E. M. Keramidas & S. M. Kaufman, pp. 156–163.
Gibbs, M. J., Armstrong, J. S., & Gibbs, A. J. (2000). Sister-scanning: a Monte Carlo procedure for assessing signals in recombinant sequences. Bioinformatics, 16, 573–582.CrossRefGoogle ScholarPubMed
Gibbs, M. J. & Weiller, G. F. (1999). Evidence that a plant virus switched hosts to infect a vertebrate and then recombined with a vertebrate-infecting virus. Proceedings of the National Academy of Sciences, USA, 96, 8022–8027.CrossRefGoogle ScholarPubMed
Gillespie, J. H. (1984). The molecular clock may be an episodic clock. Proceedings of the National Academy of Sciences, USA, 81(24), 8009–8013.CrossRefGoogle ScholarPubMed
Gillespie, J. H. (1991). The Causes of Molecular Evolution. Oxford, UK: Oxford University Press.Google Scholar
Gogarten, J. P., Kibak, H., Dittrich, P.et al. (1989). Evolution of the vacuolar H+ -ATPase: implications for the origin of eukaryotes. Proceedings of the National Academy of Sciences, USA, 86, 6661–6665.CrossRefGoogle ScholarPubMed
Goldman, N. (1993). Statistical tests of models of DNA substitution. Journal of Molecular Evolution, 36(2), 182–198.CrossRefGoogle ScholarPubMed
Goldman, N. & Yang, Z. (1994). A codon-based model of nucleotide substitution for protein-coding DNA sequences. Molecular Biology and Evolution, 11(5), 725–736.Google ScholarPubMed
Goldman, N., Anderson, J. P., & Rodrigo, A. G. (2000). Likelihood-based tests of topologies in phylogenetics. Systematic Biology, 49, 652–670.CrossRefGoogle ScholarPubMed
Goloboff, P. (1999). Analyzing large data sets in reasonable times: Solutions for composite optima. Cladistics, 15, 415–428.CrossRefGoogle Scholar
Gonnet, G. H., Cohen, M. A., & Benner, S. A. (1992). Exhaustive matching of the entire protein sequence database. Science, 256, 1443–1445.CrossRefGoogle ScholarPubMed
Goodman, S. N. (1999). Toward evidence-based medical statistics. 1: The P value fallacy. Annals of Internal Medicine, 130, 1019–1021.Google Scholar
Gotoh, O. (1982). An improved algorithm for matching biological sequences. Journal of Molecular Biology, 162, 705–708.CrossRefGoogle ScholarPubMed
Gotoh, O. (1995). A weighting system and algorithm for aligning many phylogenetically related sequences. Computer Applications in the Biosciences, 11(5), 543–551.Google ScholarPubMed
Gotoh, O. (1996). Significant improvement in accuracy of multiple protein sequence alignments by iterative refinements as assessed by reference to structural alignments. Journal of Molecular Biology, 264, 823–838.CrossRefGoogle Scholar
Gotoh, O. (1999). Multiple sequence alignment: algorithms and applications. Advances in Biophysics, 36, 159–206.CrossRefGoogle ScholarPubMed
Graessmann, M., Graessmann, A., Cadavid, E. O.et al. (1992). Characterization of the elongation factor 1-α gene of Rhynchosciara americana. Nucleic Acids Research, 20, 3780.CrossRefGoogle ScholarPubMed
Graham, J., McNeney, B., & Seillier-Moiseiwitsch, F. (2005). Stepwise detection of recombination breakpoints in sequence alignments. Bioinformatics, 21, 589–595.CrossRefGoogle ScholarPubMed
Grassly, N. C. & Holmes, E. C. (1997). A likelihood method for the detection of selection and recombination using nucleotide sequences. Molecular Biology and Evolution, 14, 239–247.CrossRefGoogle ScholarPubMed
Gribskov, M., McLachlan, A. D., & Eisenberg, D. (1987). Profile analysis: detection of distantly related proteins. Proceedings of the National Academy of Sciences, USA, 84, 4355–4358.CrossRefGoogle ScholarPubMed
Griffiths, R. C. & Tavare, S. (1994). Sampling theory for neutral alleles in a varying environment. Philosophical Transactions of the Royal Society London B Biological Sciences, 344, 403–410.CrossRefGoogle Scholar
Guindon, S. & Gascuel, O. (2003). A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Systematic Biology, 52(5), 696–704.CrossRefGoogle ScholarPubMed
Guindon, S., Rodrigo, A. G., Dyer, K. A., & Huelsenbeck, J. P. (2004). Modeling the site-specific variation of selection patterns along lineages. Proceedings of the National Academy of Sciences, USA, 101(35), 12957–12962.CrossRefGoogle ScholarPubMed
Gumbel, E. J. (1958). Statistics of Extremes. New York, NY: Columbia University Press.Google Scholar
Hall, P. & Wilson, S. R. (1991). Two guidelines for bootstrap hypothesis testing. Biometrics, 47, 757–762.CrossRefGoogle Scholar
Hall, T. A. (1999). BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symposium Series, 41, 95–98.Google Scholar
Hancock, J. M. & Armstrong, J. S. (1994). SIMPLE34: an improved and enhanced implementation for VAX and Sun computers of the SIMPLE algorithm for analysis of clustered repetitive motifs in nucleotide sequences. Computer Applications in the Biosciences, 10, 67–70.Google Scholar
Hannaert, V., Blaauw, M., Kohl, L., Allert, S., Opperdoes, F. R., & Michels, P. A. (1992). Molecular analysis of the cytosolic and glycosomal glyceraldehyde-3-phosphate dehydrogenase in Leishmania mexicana. Molecular Biochemical Parasitology, 55, 115–126.CrossRefGoogle ScholarPubMed
Hannaert, V., Saavedra, E., Duffieux, F.et al. (2003). Plant-like traits associated with metabolism of Trypanosoma parasites. Proceedings of the National Academy of Sciences, USA, 100, 1067–1071.CrossRefGoogle ScholarPubMed
Hartigan, J. A. (1973). Minimum mutation fits to a given tree. Biometrics, 29, 53–65.CrossRefGoogle Scholar
Hartl, D. L. & Clark, A. G. (1997). Principles of Population Genetics. Sunderland, MA: Sinauer Associates, Inc.Google Scholar
Hasegawa, M. & Kishino, H. (1989). Confidence limits on the maximum-likelihood estimate of the hominid tree from mitochondrial-DNA sequences. Evolution, 43(3), 672–677.Google Scholar
Hasegawa, M., Cao, Y., & Yang, Z. (1998). Preponderance of slightly deleterious polymorphism in mitochondrial DNA: nonsynonymous/synonymous rate ratio is much higher within species than between species. Molecular Biology and Evolution, 15(11), 1499–1505.CrossRefGoogle ScholarPubMed
Hasegawa, M., Kishino, H., & Yano, T. A. (1985). Dating of the human ape splitting by a molecular clock of mitochondrial-DNA. Journal of Molecular Evolution, 22, 160–174.CrossRefGoogle ScholarPubMed
Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97–109.CrossRefGoogle Scholar
Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97–109.CrossRefGoogle Scholar
Hedges, S. B. (1992). The number of replications needed for accurate estimation of the bootstrap P value in phylogenetic studies. Molecular Biology and Evolution, 9, 366–369.Google ScholarPubMed
Hedges, S. B. (1994). Molecular evidence for the origin of birds. Proceedings of the National Academy of Sciences, USA, 91, 2621–2624.CrossRefGoogle Scholar
Hedrick, P. W. (2007). Balancing selection. Current Biology, 17(7), R230–R231.CrossRefGoogle ScholarPubMed
Hein, J. (1993). A heuristic method to reconstruct the history of sequences subject to recombination. Journal of Molecular Evolution, 36, 396–406.CrossRefGoogle Scholar
Hein, J., Schierup, M. H., & Wiuf, C. (2005). Gene Genealogies, Variation and Evolution. Oxford, UK: Oxford University Press.Google Scholar
Hendy, M. D. & Penny, D. (1982). Branch-and-bound algorithms to determine minimal evolutionary trees. Mathematical Biosciences, 59, 277–290.CrossRefGoogle Scholar
Hendy, M. D. & Penny, D. (1993). Spectral analysis of phylogenetic data. Journal of Classification, 10, 5–24.CrossRefGoogle Scholar
Henikoff, S. & Henikoff, J. G. (1992). Amino acid substitution matrices from protein blocks. Proceedings of the National Academy of Sciences, USA, 89(22), 10915–10919.CrossRefGoogle ScholarPubMed
Hill, W. G. & Robertson, A. (1966). The effect of linkage on limits to artificial selection. Genetical Research, 8, 269–294.CrossRefGoogle ScholarPubMed
Hillis, D. M. (1996). Inferring complex phylogenies. Nature, 383, 130.CrossRefGoogle ScholarPubMed
Hillis, D. M. & Bull, J. J. (1993). An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis. Systematic Biology, 42, 182–192.CrossRefGoogle Scholar
Hillis, D. M., Huelsenbeck, J. P., & Swofford, D. L. (1994). Hobgoblin of phylogenetics. Nature, 369, 363–364.CrossRefGoogle ScholarPubMed
Hillis, D. M., Moritz, C., & Mable, B. K. (1996). Molecular Systematics. Sunderland, MA: Sinauer Associates.Google Scholar
Hoeting, J. A., Madigan, D., & Raftery, A. E. (1999). Bayesian model averaging: a tutorial. Statistical Science, 14(4), 382–417.Google Scholar
Hogeweg, P. & Hesper, B. (1984). The alignment of sets of sequences and the construction of phylogenetic trees. An integrated method. Journal of Molecular Evolution, 20, 175–186.CrossRefGoogle Scholar
Holland, B. & Moulton, V. (2003). Consensus networks: a method for visualising incompatibilities in collections of trees. In Proceedings of the 3rd Workshop on Algorithms in Bioinformatics (WABI'03), Volume 2812 of Lecture Notes in Bioinformatics, ed. Benson, G. & Page, R., pp. 165–176. Berlin/Heidelberg, Germany: Springer-Verlag.Google Scholar
Holland, B., Huber, K., Moulton, V., & Lockhart, P. (2004). Using consensus networks to visualize contradictory evidence for species phylogeny. Molecular Biology and Evolution, 21, 1459–1461.CrossRefGoogle ScholarPubMed
Holland, B., Delsuc, F., & Moulton, V. (2005). Visualizing conflicting evolutionary hypotheses in large collections of trees using consensus networks. Systematic Biology, 54, 56–65.CrossRefGoogle ScholarPubMed
Holmes, E. C., Worobey, M., & Rambaut, A. (1999). Phylogenetic evidence for recombination in dengue virus. Molecular Biology and Evolution, 16, 405–409.CrossRefGoogle ScholarPubMed
Holmes, E. C., Zhang, L. Q., Simmonds, P., Ludlam, C. A., & Brown, A. J. L. (1992). Convergent and divergent sequence evolution in the surface envelope glycoprotein of human-immunodeficiency-virus type-1 within a single infected patient. Proceedings of the National Academy of Sciences, USA, 89(11), 4835–4839.CrossRefGoogle ScholarPubMed
Hordijk, W. & Gascuel, O. (2006). Improving the efficiency of SPR moves in phylogenetic tree search methods based on maximum likelihood. Bioinformatics, 21, 4338–4347.CrossRefGoogle Scholar
Huang, X. (1994). On global sequence alignment. Computer Applications in the Biosciences, 10(3), 227–235.Google ScholarPubMed
Huber, K. & Moulton, V. (2005). Phylogenetic networks. In Mathematics of Evolution and Phylogeny, ed. Gascuel, O., pp. 178–204. Oxford, UK: Oxford University Press.Google Scholar
Huber, K., Moulton, V., Lockhart, P., & Dress, A. (2001). Pruned median networks: a technique for reducing the complexity of median networks. Molecular Phylogenetics and Evolution, 19, 302–310.CrossRefGoogle ScholarPubMed
Huber, T., Faulkner, G., & Hugenholtz, P. (2004). Bellerophon: a program to detect chimeric sequences in multiple sequence alignments. Bioinformatics, 20, 2317–2319.CrossRefGoogle ScholarPubMed
Hudson, R. R. (1985). The sampling distribution of linkage disequilibrium under an infinite allele model without selection. Genetics, 109, 611–631.Google ScholarPubMed
Hudson, R. R. & Kaplan, N. L. (1988). The coalescent process in models with selection and recombination. Genetics, 120, 831–840.Google Scholar
Huelsenbeck, J. P. & Crandall, K. A. (1997). Phylogeny estimation and hypothesis testing using maximum likelihood. Annual Reviews of Ecology Systems, 28, 437–466.CrossRefGoogle Scholar
Huelsenbeck, J. P. & Dyer, K. A. (2004). Bayesian estimation of positively selected sites. Journal of Molecular Evolution, 58(6), 661–672.CrossRefGoogle ScholarPubMed
Huelsenbeck, J. P. & Hillis, D. M. (1993). Success of phylogenetic methods in the four-taxon case. Systematic Biology, 42, 247–264.CrossRefGoogle Scholar
Huelsenbeck, J. P. & Rannala, B. (2004). Frequentist properties of Bayesian posterior probabilities of phylogenetic trees under simple and complex substitution models. Systematic Biology, 53(6), 904–913.CrossRefGoogle ScholarPubMed
Huelsenbeck, J. P. & Ronquist, F. (2001). MrBayes: Bayesian inference of phylogenetic trees. Bioinformatics, 17, 754–755.CrossRefGoogle ScholarPubMed
Huelsenbeck, J. P. & Ronquist, F. (2005). Bayesian analysis of molecular evolution using MrBayes. In Statistical Methods in Molecular Evolution, ed. Nielsen, R., pp. 183–232. New York: Springer.CrossRefGoogle Scholar
Huelsenbeck, J. P., Jain, S., Frost, S. W. D., & Kosakovsky Pond, S. L. (2006). A Dirichlet process model for detecting positive selection in protein-coding DNA sequences. Proceedings of the National Academy of Sciences, USA, 103(16), 6263–6268.CrossRefGoogle ScholarPubMed
Huelsenbeck, J. P., Larget, B., & Alfaro, M. E. (2004). Bayesian phylogenetic model selection using reversible jump Markov chain Monte Carlo. Molecular Biology and Evolution, 21(6), 1123–1133.CrossRefGoogle ScholarPubMed
Hughes, A. L. & Yeager, M. (1997). Comparative evolutionary rates of introns and exons in murine rodents. Journal of Molecular Evolution, 45(2), 125–130.CrossRefGoogle ScholarPubMed
Hughey, R. & Krogh, A. (1996). Hidden Markov models for sequence analysis: extension and analysis of the basic method. Computer Applications in the Biosciences, 12(2), 95–107.Google ScholarPubMed
Husmeier, D. (2005). Discriminating between rate heterogeneity and interspecific recombination in DNA sequence alignments with phylogenetic factorial hidden Markov models. Bioinformatics, 21, 166–172.CrossRefGoogle ScholarPubMed
Husmeier, D. & McGuire, G. (2003). Detecting recombination in 4-taxa DNA sequence alignments with Bayesian hidden Markov models and Markov chain Monte Carlo. Molecular Biology and Evolution, 20, 315–337.CrossRefGoogle ScholarPubMed
Husmeier, D. & Wright, F. (2001a). Detection of recombination in DNA multiple alignments with hidden Markov models. Journal of Computing Biology, 8, 401–427.CrossRefGoogle ScholarPubMed
Husmeier, D. & Wright, F. (2001b). Probabilistic divergence measures for detecting interspecies recombination. Bioinformatics, 17, S123–S131.CrossRefGoogle ScholarPubMed
Huson, D. (1998). SplitsTree: a program for analyzing and visualizing evolutionary data. Bioinformatics, 14, 68–73.CrossRefGoogle ScholarPubMed
Huson, D. & Dress, A. (2004). Constructing split graphs, IEEE Transactions on Computational Biology and Bioinformatics, 1, 109–115.Google Scholar
Huson, D. & Bryant, D. (2006). Application of phylogenetic networks in evolutionary studies. Molecular Biology and Evolution, 23, 254–267.CrossRefGoogle ScholarPubMed
Huson, D., Dezulian, T., Kloepper, T., & Steel, M. (2004). Phylogenetic super-networks from partial trees. IEEE Transactions on Computational Biology and Bioinformatics, 1, 151–158.CrossRefGoogle ScholarPubMed
Ina, Y. (1995). New methods for estimating the numbers of synonymous and nonsynonymous substitutions. Journal of Molecular Evolution, 40(2), 190–226.CrossRefGoogle ScholarPubMed
Ingman, M., Kaessmann, H., Paabo, S., & Gyllensten, U. (2000). Mitochondrial genome variation and the origin of modern humans. Nature, 408(6813), 708–713.CrossRefGoogle ScholarPubMed
Jakobsen, I. B. & Easteal, S. (1996). A program for calculating and displaying compatibility matrices as an aid in determining reticulate evolution in molecular sequences. Computing in Applied Biosciences, 12, 291–295.Google ScholarPubMed
Jakobsen, I. B., Wilson, S. R., & Easteal, S. (1997). The partition matrix: exploring variable phylogenetic signals along nucleotide sequence alignments. Molecular Biology and Evolution, 14, 474–484.CrossRefGoogle ScholarPubMed
Jeffreys, A. J., Murray, J., & Neumann, R. (1998). High-resolution mapping of crossovers in human sperm defines a minisatellite-associated recombination hotspot. Molecular Cell, 2, 267–273.CrossRefGoogle ScholarPubMed
Jeffreys, A. J., Ritchie, A., & Neumann, R. (2000). High resolution analysis of haplotype diversity and meiotic crossover in the human TAP2 recombination hotspot. Human Molecular Genetics, 9, 725–733.CrossRefGoogle ScholarPubMed
Jenkins, G. M., Rambaut, A., Pybus, O. G., & Holmes, E. C. (2002). Rates of molecular evolution in RNA viruses: a quantitative phylogenetic analysis. Journal of Molecular Evolution, 54(2), 156–165.CrossRefGoogle ScholarPubMed
Jensen, J. D., Kim, Y., DuMont, V. B., Aquadro, C. F., & Bustamante, C. D. (2005). Distinguishing between selective sweeps and demography using DNA polymorphism data. Genetics, 170, 1401–1410.CrossRefGoogle ScholarPubMed
Johnson, J. B. & Omland, K. S. (2004). Model selection in ecology and evolution. TREE, 19, 101–108.Google ScholarPubMed
Jolley, K. A., Feil, E. J., Chan, M. S., & Maiden, M. C. (2001). Sequence type analysis and recombinational tests (START). Bioinformatics, 17, 1230–1231.CrossRefGoogle Scholar
Jones, D. T., Taylor, W. R., & Thornton, J. M. (1992). The rapid generation of mutation data matrices from protein sequences. Computer Applications in the Biosciences, 8, 275–282.Google ScholarPubMed
Jukes, T. H. & Cantor, C. R. (1969). Evolution of protein molecules. In Mammalian Protein Metabolism, ed. Munro, H. H., Vol. III, pp. 21–132. New York: Academic Press.CrossRefGoogle Scholar
Kaplan, N. L. & Hudson, R. R. (1985). The use of sample genealogies for studying a selectively neutral m-loci model with recombination. Theoretical Population Biology, 28, 382–396.CrossRefGoogle ScholarPubMed
Karlin, S. & Altschul, S. F. (1990). Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proceedings of the National Academy of Sciences, USA, 87, 2264–2268.CrossRefGoogle ScholarPubMed
Karlin, S. & Altschul, S. F. (1993). Applications and statistics for multiple high-scoring segments in molecular sequences. Proceedings of the National Academy of Sciences, USA, 90, 5873–5877.CrossRefGoogle ScholarPubMed
Kass, R. E. & Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90(430), 773–795.CrossRefGoogle Scholar
Katoh, K., Misawa, K., Kuma, K., & Miyata, T. (2002). MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Research, 30(14), 3059–3066.CrossRefGoogle ScholarPubMed
Katoh, K., Kuma, K., Toh, H., & Miyata, T. (2005). MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucleic Acids Research, 33(2), 511–518.CrossRefGoogle ScholarPubMed
Kececioglu, J. (1993). The maximum weight trace problem in multiple sequence alignment. Proceedings of the 4th Symposium on Combinatorial Pattern Matching, Springer-Verlag Lecture Notes in Computer Science, 684, 106–119.CrossRefGoogle Scholar
Kent, W. J. (2002). BLAT – the BLAST-like alignment tool. Genome Research, 12, 656–664.CrossRefGoogle ScholarPubMed
Kidd, K. K. & Sgaramella-Zonta, L. A. (1971). Phylogenetic analysis: Concepts and methods. American Journal of Human Genetics, 23, 235–252.Google ScholarPubMed
Kim, H., Feil, I. K., Verlinde, C. L. M. J., Petra, P. H., & Hol, W. G. J. (1995). Crystal structure of glycosomal glyceraldehyde-3-phosphate dehydrogenase from Leishmania mexicana: implications for structure-based drug design and a new position for the inorganic phosphate binding site. Biochemistry, 34, 14975–14986.CrossRefGoogle Scholar
Kimura, M. (1968). Evolutionary rate at the molecular level. Nature, 217, 624–626.CrossRefGoogle ScholarPubMed
Kimura, M. (1969a). The number of heterozygous nucleotide sites maintained in a finite population due to steady flux of mutations. Genetics, 61, 893–903.Google Scholar
Kimura, M. (1969b). The rate of molecular evolution considered from the standpoint of population genetics. Proceedings of the National Academy of Sciences, USA, 63, 1181–1188.CrossRefGoogle ScholarPubMed
Kimura, M. (1980). A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. Journal of Molecular Evolution, 16, 111–120.CrossRefGoogle ScholarPubMed
Kimura, M. (1981). Estimation of evolutionary distances between homologous nucleotide sequences. Proceedings of the National Academy of Sciences, USA, 78(1), 454–458.CrossRefGoogle ScholarPubMed
Kimura, M. (1983). The Neutral Theory of Molecular Evolution. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Kimura, M. & Ohta, T. (1971). Protein polymorphism as a phase of molecular evolution. Nature, 229, 467–479.CrossRefGoogle ScholarPubMed
Kimura, M. & Ohta, T. (1972). On the stochastic model for estimation of mutational distance between homologous proteins. Journal of Molecular Evolution, 2, 87–90.CrossRefGoogle ScholarPubMed
King, J. L. & Jukes, T. H. (1969). Non-Darwinian evolution. Science, 164, 788–798.CrossRefGoogle ScholarPubMed
Kingman, J. F. C. (1982a). The coalescent. Stochastic Processes and Their Applications, 13, 235–248.CrossRefGoogle Scholar
Kingman, J. F. C. (1982b). On the genealogy of large populations. Journal of Applied Probability, 19A, 27–43.CrossRefGoogle Scholar
Kingman, J. F. C. (2000). Origins of the coalescent, 1974–1982. Genetics, 156, 1461–1463.Google ScholarPubMed
Kirkpatrick, S., Gelatt, Jr., C. D., & Vecchi, M. P. (1983). Optimisation using simulated annealing. Science, 220, 671–680.CrossRefGoogle Scholar
Kiryu, H., Tabei, Y., Kin, T., & Asai, K. (2007). Murlet: a practical multiple alignment tool for structural RNA sequences. Bioinformatics, 23, 1588–1589.CrossRefGoogle ScholarPubMed
Kishino, H. & Hasegawa, M. (1989). Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea. Journal of Molecular Evolution, 29, 170–179.CrossRefGoogle ScholarPubMed
Kishino, H., Miyata, T., & Hasegawa, M. (1990). Maximum likelihood inference of protein phylogeny and the origin of chloroplasts. Journal of Molecular Evolution, 31, 151–160.CrossRefGoogle Scholar
Kishino, H., Thorne, J. L., & Bruno, W. J. (2001). Performance of a divergence time estimation method under a probabilistic model of rate evolution. Molecular Biology of Evolution, 18(3), 352–361.CrossRefGoogle Scholar
Klotz, L. C., Blanken, R. L., Komar, N., & Mitchell, R. M. (1979). Calculation of evolutionary trees from sequence data. Proceedings of the National Academy of Sciences, USA, 76, 4516–4520.CrossRefGoogle ScholarPubMed
Kluge, A. G. & Farris, J. S. (1969). Quantitative phyletics and the evolution of anurans. Systematic Zoology, 18, 1–32.CrossRefGoogle Scholar
Korber, B., Muldoon, M., Theiler, J.et al. (2000). Timing the ancestor of the HIV-1 pandemic strains. Science, 288(5472), 1789–1796.CrossRefGoogle ScholarPubMed
Korf, I., Yandell, M., & Bedell, J. (2003). BLAST. Sebastopol CA, USA: O'Reilly.Google ScholarPubMed
Korostensky, C. & Gonnet, G. H. (1999). Proceedings of the String Processing and Information Retrieval Symposium and International Workshop on Groupwave, Cancun, Mexico, p. 105.Google Scholar
Kosakovsky Pond, S. L. & Frost, S. D. W. (2005a). A simple hierarchical approach to modeling distributions of substitution rate. Molecular Biology and Evolution, 22, 223–234.CrossRefGoogle Scholar
Kosakovsky Pond, S. L. & Frost, S. D. W. (2005b). A genetic algorithm approach to detecting lineage-specific variation in selection pressure. Molecular Biology and Evolution, 22(3), 478–485.CrossRefGoogle ScholarPubMed
Kosakovsky Pond, S. L. & Frost, S. D. W. (2005c). Not so different after all: a comparison of methods for detecting amino-acid sites under selection. Molecular Biology and Evolution, 22, 1208–1222.CrossRefGoogle ScholarPubMed
Kosakovsky Pond, S. L. & Muse, S. V. (2004). Column sorting: rapid calculation of the phylogenetic likelihood function. Systems in Biology, 53(5), 685–692.CrossRefGoogle ScholarPubMed
Kosakovsky Pond, S. L. & Muse, S. V. (2005). Site-to-site variation of synonymous substitution rates. Molecular Biology and Evolution, 22(12), 2375–2385.CrossRefGoogle Scholar
Kosakovsky Pond, S. L., Frost, S. D. W., & Muse, S. V. (2005). HyPhy: Hypothesis testing using phylogenies. Bioinformatics, 21(5), 676–679.CrossRefGoogle Scholar
Kosakovsky Pond, S. L., Frost, S. D. W., Grossman, Z., Gravenor, M. B., Richman, D. D., & Leigh Brown, A. J. (2006a). Adaptation to different human populations by HIV-1 revealed by codon-based analyses. PLoS Comparative Biology, 23, 2993–3000.Google Scholar
Kosakovsky Pond, S. L., Frost, S. D., & Muse, S. V. (2005). HyPhy: hypothesis testing using phylogenies. Bioinformatics, 21(5), 676–679.CrossRefGoogle Scholar
Kosakovsky Pond, S. L., Posada, D., Gravenor, M. B., Woelk, C. H., & Frost, S. D. W. (2006b). GARD: a genetic algorithm for recombination detection. Bioinformatics, 22, 3096–3098.CrossRefGoogle Scholar
Kosakovsky Pond, S. L., Posada, D., Gravenor, M. B., Woelk, C. H., & Frost, S. D. W. (2006c). Automated phylogenetic detection of recombination using a genetic algorithm. Molecular Biology and Evolution, 23(10), 1891–1901.CrossRefGoogle ScholarPubMed
Kotetishvili, M., Syine, O. C., Kreger, A., Morris, Jr, J. G., & Sulakvelidze, A. (2002). Multilocus sequence typing for characterization of clinical and environmental Salmonella strains. Journal of Clinical Microbiology, 40(5), 1626–1635.CrossRefGoogle ScholarPubMed
Krogh, A., Brown, M., Mian, I. S., Sjolander, K., & Haussler, D. (1994). Hidden Markov models in computational biology: applications to protein modeling. Journal of Molecular Biology, 235, 1501–1531.CrossRefGoogle ScholarPubMed
Krone, S. M. & Neuhauser, C. (1997). Ancestral processes with selection. Theoretical Population Biology, 51, 210–237.CrossRefGoogle ScholarPubMed
Kuhner, M. K. (2006). LAMARC 2.0: Maximum likelihood and Bayesian estimation of population parameters. Bioinformatics, 22(6), 768–770.CrossRefGoogle ScholarPubMed
Kuhner, M. K. & Felsenstein, J. (1994). A simulation comparison of phylogeny algorithms under equal and unequal evolutionary rates. Molecular Biology and Evolution, 11, 459–468.Google ScholarPubMed
Kuhner, M. K. & Smith, L. P. (2007). Comparing likelihood and Bayesian coalescent estimators of population parameters. Genetics, 175, 155–165.CrossRefGoogle Scholar
Kuhner, M. K., Yamato, J., & Felsenstein, J. (1995). Estimating effective population size and mutation rate from sequence data using Metropolis–Hastings sampling. Genetics, 140, 1421–1430.Google ScholarPubMed
Kuhner, M. K., Yamato, J., & Felsenstein, J. (1998). Maximum likelihood estimation of population growth rates based on the coalescent. Genetics, 149, 429–434.Google ScholarPubMed
Kuhner, M. K., Yamato, J., & Felsenstein, J. (2000). Maximum likelihood estimation of recombination rates from population data. Genetics, 156, 1393–1401.Google ScholarPubMed
Kullback, S. & Leibler, R. A. (1951). On information and sufficiency. Annals of Mathematical Statistics, 22(1), 79–86.CrossRefGoogle Scholar
Kumar, S. (1996). A stepwise algorithm for finding minimum-evolution trees. Molecular Biology and Evolution, 13, 584–593.CrossRefGoogle ScholarPubMed
Kumar, S., Tamura, K., & Nei, M. (1994). Mega: molecular evolutionary genetics analysis software for microcomputers. Bioinformatics, 10(2), 189–191.CrossRefGoogle ScholarPubMed
Kyte, J. & Doolittle, R. F. (1982). A simple method for displaying the hydropathic character of a protein. Journal of Molecular Biology, 157, 105–132.CrossRefGoogle ScholarPubMed
Lanave, C., Preparata, G., Saccone, C., & Serio, G. (1984). A new method for calculating evolutionary substitution rates. Journal of Molecular Evolution, 20, 86–93.CrossRefGoogle ScholarPubMed
Lanciotti, R. S., Gubler, D. J., & Trent, D. W. (1997). Molecular evolution and phylogeny of dengue-4 viruses. Journal of General Virology, 78, 2279–2284.CrossRefGoogle ScholarPubMed
Lartillot, N. & Philippe, H. (2006). Determining Bayes factors using thermodynamic integration. Systematic Biology, 55, 195–207.CrossRefGoogle Scholar
Lassmann, T. & Sonnhammer, E. L. (2005). Kalign – an accurate and fast multiple sequence alignment algorithm. BMC Bioinformatics, 6, 298.CrossRefGoogle ScholarPubMed
Lee, C., Grasso, C., & Sharlow, M. F. (2002). Multiple sequence alignment using partial order graphs. Bioinformatics, 18(3), 452–464.CrossRefGoogle ScholarPubMed
Legendre, P. & Makarenkov, V. (2002). Reconstruction of biogeographic and evolutionary networks using reticulograms. Systematic Biology, 51, 199–216.CrossRefGoogle ScholarPubMed
Lemey, P., Pybus, O. G., Rambaut, A.et al. (2004). The molecular population genetics of HIV-1 group O. Genetics, 167, 1059–1068.CrossRefGoogle ScholarPubMed
Lemey, P., Rambaut, A., & Pybus, O. G. (2006). HIV evolutionary dynamics within and among hosts. AIDS Reviews, 8, 155–170.Google ScholarPubMed
Lemmon, A. R. & Milinkovitch, M. C. (2002). The metapopulation genetic algorithm: an efficient solution for the problem of large phylogeny estimation. Proceedings of the National Academy Sciences, USA, 99, 10516–10521.CrossRefGoogle ScholarPubMed
Lemey, P., Kosakovsky Pond, S. L., Drummond, A. J., Pybus, O.et al. (2007). Synonymous substitution rates predict HIV disease progression as a result of underlying replication dynamics. PLoS Comparative Biology, 3(2).CrossRefGoogle ScholarPubMed
Lenstra, J. A., Vliet, A., Carnberg, A. C., Hemert, F. J., & Mler, W. (1986). Genes coding for the elongation factor EF-1α in Artemia. European Journal of Biochemistry, 155, 475–483.CrossRefGoogle ScholarPubMed
Lewis, P. O. (1998). A genetic algorithm for maximum likelihood phylogeny inference using nucleotide-sequence data. Molecular Biology and Evolution, 15, 277–283.CrossRefGoogle ScholarPubMed
Li, W. H. (1981). Simple method for constructing phylogenetic trees from distance matrixes. Proceedings of the National Academy of Sciences of the USA, 78, 1085–1089.CrossRefGoogle Scholar
Li, W. H. (1993). Unbiased estimation of the rates of synonymous and nonsynonymous substitution. Journal of Molecular Evolution, 36(1), 96–99.CrossRefGoogle ScholarPubMed
Li, W. H. (1997). Molecular Evolution. Sunderland, MA: Sinauer Associates.Google ScholarPubMed
Li, W. H., Gojobori, T., & Nei, M. (1981). Pseudogenes as a paradigm of neutral evolution. Nature, 292(5820), 237–239.CrossRefGoogle ScholarPubMed
Li, W. H., Wu, C. I., & Luo, C. C. (1985). A new method for estimating synonymous and nonsynonymous rates of nucleotide substitution considering the relative likelihood of nucleotide and codon changes. Molecular Biology and Evolution, 2(2), 150–174.Google ScholarPubMed
Lindgren, B. W. (1976). Statistical Theory. 3rd edn., New York: Macmillan.Google Scholar
Linnaeus, C. (1758). Systema Naturae. 10th edn. Stockholm.Google Scholar
Liò, P. & Goldman, N. (1998). Models of molecular evolution and phylogeny. Genome Research, 8(12), 1233–1244.CrossRefGoogle ScholarPubMed
Lipman, D. J., Altschul, S. F., & Kececioglu, J. D. (1989). A tool for multiple sequence alignment. Proceedings of the National Academy of Sciences, USA, 86, 4412–4415.CrossRefGoogle ScholarPubMed
Lockart, P. J., Steel, M. D., Hendy, M. D., & Penny, D. (1994). Recovering evolutionary trees under a more realistic model of evolution. Molecular Biology and Evolution, 11, 605–612.Google Scholar
Lockhart, P., Penny, D., & Meyer, A. (1995). Testing the phylogeny of swordtail fishes using split decomposition and spectral analysis. Journal of Molecular Evolution, 41, 666–674.CrossRefGoogle Scholar
Lockhart, P. J., Penny, D., Hendy, M. D., Howe, C. J., Beanland, T. J., & Larkum, A. W. (1992). Controversy on chloroplast origins. FEBS Letters, 301, 127–131.CrossRefGoogle ScholarPubMed
Lockhart, P. J., Steel, M. A., Hendy, M. D., & Penny, D. (1994). Recovering evolutionary trees under a more realistic model of sequence evolution. Molecular Biology and Evolution, 11, 605–612.Google Scholar
Lole, K. S., Bollinger, R. C., Paranjape, R. S.et al. (1999). Full-length human immunodeficiency virus type 1 genomes from subtype C-infected seroconverters in India, with evidence of intersubtype recombination. Journal of Virology, 73, 152–160.Google ScholarPubMed
Lopez, P., Forterre, P., & Philippe, H. (1999). The root of the tree of life in the light of the covarion model. Journal of Molecular Evolution, 49, 496–508.CrossRefGoogle ScholarPubMed
Lundy, M. (1985). Applications of the annealing algorithm to combinatorial problems in statistics. Biometrika, 72, 191–198.CrossRefGoogle Scholar
Lunter, G., Miklos, I., Drummond, A., Jensen, J. L., & Hein, J. (2005). Bayesian coestimation of phylogeny and sequence alignment. BMC Bioinformatics, 6(1), 83.CrossRefGoogle ScholarPubMed
Lyons-Weiler, J., Hoelzer, G. A., & Tausch, R. J. (1996). Relative Apparent Synapomorphy Analysis (RASA) I: the statistical measurement of phylogenetic signal. Molecular Biology and Evolution, 13, 749–757.CrossRefGoogle ScholarPubMed
Maddison, D. R. (1991). The discovery and importance of multiple islands of most parsimonious trees. Systematic Zoology, 40, 315–328.CrossRefGoogle Scholar
Maddison, W. P. & Maddison, D. R. (1989). Interactive analysis of phylogeny and character evolution using the computer program MacClade. Folia Primatologia (Basel), 53(1–4), 190–202.CrossRefGoogle ScholarPubMed
Maddison, D. R., Swofford, D. L., & Maddison, W. P. (1997). NEXUS: an extensible file format for systematic information. Systematic Biology, 46(4), 590–621.CrossRefGoogle ScholarPubMed
Madigan, D. M. & Raftery, A. E. (1994). Model selection and accounting for model uncertainty in graphical models using Occam's Window. Journal of the American Statistical Association, 89, 1335–1346.CrossRefGoogle Scholar
Mailund, T. & Pedersen, C. N. (2004). QuickJoin – fast neighbour-joining tree reconstruction. Bioinformatics, 20(17), 3261–3262.CrossRefGoogle ScholarPubMed
Martin, D. & Rybicki, E. (2000). RDP: detection of recombination amongst aligned sequences. Bioinformatics, 16, 562–563.CrossRefGoogle ScholarPubMed
Martin, D. P., Posada, D., Crandall, K. A., & Williamson, C. (2005a). A modified bootscan algorithm for automated identification of recombinant sequences and recombination breakpoints. AIDS Research Human Retroviruses, 21, 98–102.CrossRefGoogle ScholarPubMed
Martin, D. P., Walt, E., Posada, D., & Rybicki, E. P. (2005b). The evolutionary value of recombination is constrained by genome modularity. PLoS Genetics, 1(4), e51.CrossRefGoogle ScholarPubMed
Martin, D. P., Williamson, C., & Posada, D. (2005). RDP2: recombination detection and analysis from sequence alignments. Bioinformatics, 21, 260–262.CrossRefGoogle ScholarPubMed
Matsuda, H. (1995). Construction of phylogenetic trees from amino acid sequences using a genetic algorithm. In Proceedings of the Genome Informatics Workshop VI, ed. Hagiya, M., Suyama, A., Takagi, T., Nakai, K., Miyano, S., & Yokomori, T., pp. 19–28. Tokyo: Universal Academy Press.Google Scholar
Maydt, J. & Lengauer, T. (2006). Recco: recombination analysis using cost optimization. Bioinformatics, 22, 1064–1071.CrossRefGoogle ScholarPubMed
Maynard Smith, J. & Smith, N. H. (1998). Detecting recombination from gene trees. Molecular Biology and Evolution, 15, 590–599.CrossRefGoogle ScholarPubMed
Maynard Smith, J. (1992). Analyzing the mosaic structure of genes. Journal of Molecular Evolution, 34, 126–129.Google Scholar
Maynard-Smith, J. (1970). Population size, polymorphism, and the rate of non-Darwinian evolution. American Naturalist, 104, 231–236.CrossRefGoogle Scholar
McDonald, J. H. & Kreitman, M. (1991). Adaptive protein evolution at the Adh locus in Drosophila. Nature, 351(6328), 652–654.CrossRefGoogle ScholarPubMed
McGinnis, S. & Madden, T. L. (2004). BLAST: at the core of a powerful and diverse set of sequence analysis tools. Nucleic Acids Research, 32, W20–W25.CrossRefGoogle ScholarPubMed
McGuire, G. & Wright, F. (2000). TOPAL 2.0: Improved detection of mosaic sequences within multiple alignments. Bioinformatics, 16, 130–134.CrossRefGoogle ScholarPubMed
McGuire, G., Wright, F., & Prentice, M. J. (1997). A graphical method for detecting recombination in phylogenetic data sets. Molecular Biology and Evolution, 14, 1125–1131.CrossRefGoogle ScholarPubMed
McLaughlin, P. J. & Dayhoff, M. O. (1973). Eukaryote evolution: a view based on cytochrome c sequence data. Journal of Molecular Evolution, 2, 99–116.CrossRefGoogle ScholarPubMed
McVean, G. A. T. & Charlesworth, B. (2000). The effects of Hill–Robertson interference between weakly selected mutations on patterns of molecular evolution and variation. Genetics, 155(2), 929–944.Google ScholarPubMed
McVean, G., Awadalla, P., & Fearnhead, P. (2002). A coalescent-based method for detecting and estimating recombination from gene sequences. Genetics, 160, 1231–1241.Google ScholarPubMed
Messier, W. & Stewart, C.-B. (1997). Episodic adaptive evolution of primate lysozymes. Nature, 385, 151–154.CrossRefGoogle ScholarPubMed
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953). Equation of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–1092.CrossRefGoogle Scholar
Metz, E. C., Robles-Sikisaka, R., & Vacquier, V. D. (1998). Nonsynonymous substitution in abalone sperm fertilization genes exceeds substitution in introns and mitochondrial DNA. Proceedings of the National Academy of Sciences, USA, 95(18), 10676–10681.CrossRefGoogle ScholarPubMed
Milne, I., Wright, F., Rowe, G., Marshall, D. F., Husmeier, D., & McGuire, G. (2004). TOPALi: software for automatic identification of recombinant sequences within DNA multiple alignments. Bioinformatics, 20, 1806–1807.CrossRefGoogle ScholarPubMed
Minin, V., Abdo, Z., Joyce, P., & Sullivan, J. (2003). Performance-based selection of likelihood models for phylogeny estimation. Systematic Biology, 52(5), 674–683.CrossRefGoogle ScholarPubMed
Minin, V. N., Dorman, K. S., Fang, F.et al. (2005). Dual multiple change-point model leads to more accurate recombination detection. Bioinformatics, 21, 3034–3042.CrossRefGoogle ScholarPubMed
Minin, V. N., Dorman, K. S., Fang, F., & Suchard, M. A. (2007). Phylogenetic mapping of recombination hotspots in human immunodeficiency virus via spatially smoothed change-point processes. Genetics, 175, 1773–1785.CrossRefGoogle ScholarPubMed
Miralles, R., Gerrish, P. J., Moya, A., & Elena, S. F. (1999). Clonal interference and the evolution of RNA viruses. Science, 285(5434), 1745–1747.CrossRefGoogle ScholarPubMed
Miyata, T. & Yasunaga, T. (1980). Molecular evolution of mRNA: a method for estimating evolutionary rates of synonymous and amino acid substitutions from homologous nucleotide sequences and its application. Journal of Molecular Evolution, 16(1), 23–36.CrossRefGoogle ScholarPubMed
Moilanen, A. (2001). Simulated evolutionary optimization and local search: Introduction and application to tree search. Cladistics, 17, S12–S25.CrossRefGoogle Scholar
Moore, C. B., John, M., James, I. R., Christiansen, F. T., Witt, C. S., & Mallal, S. A. (2002). Evidence of HIV-1 adaptation to HLA-restricted immune responses at a population level. Science, 296(5572), 1439–1443.CrossRefGoogle Scholar
Morgenstern, B. (1999). DIALIGN2: improvement of the segment-to-segment approach to multiple sequence alignment. Bioinformatics, 15, 211–218.CrossRefGoogle Scholar
Morgenstern, B. (2004). DIALIGN: multiple DNA and protein sequence alignment at BiBiServ. Nucleic Acids Research, 32(Web Server issue), W33–W36.CrossRefGoogle ScholarPubMed
Morgenstern, B., Dress, A., & Werner, T. (1996). Multiple DNA and protein sequence alignment based on segment-to-segment comparison. Proceedings of the National Academy of Sciences, USA, 93(22), 12098–12103.CrossRefGoogle ScholarPubMed
Morgenstern, B., Goel, S., Sczyrba, A., & Dress, A. (2003). AltAVisT: comparing alternative multiple sequence alignments. Bioinformatics, 19(3), 425–426.CrossRefGoogle ScholarPubMed
Morgenstern, B., Prohaska, S. J., Pohler, D., & Stadler, P. F. (2006). Multiple sequence alignment with user-defined anchor points. Algorithms Molecular Biology, 1(1), 6.CrossRefGoogle ScholarPubMed
Morrison, D. (2005). Networks in phylogenetic analysis: new tools for population biology, International Journal of Parasitology, 35, 567–582.CrossRefGoogle ScholarPubMed
Moulton, V. & Steel, M. (1999). Retractions of finite distance functions onto tree metrics. Discrete Applied Mathematics, 91, 215–233.CrossRefGoogle Scholar
Muller, H. J. (1932). Some genetic aspects of sex. American Naturalist, 66, 118–138.CrossRefGoogle Scholar
Muller, T. & Vingron, M. (2000). Modeling amino acid replacement. Journal of Computational Biology, 7(6), 761–776.CrossRefGoogle ScholarPubMed
Muse, S. V. (1996). Estimating synonymous and nonsynonymous substitution rates. Molecular Biology and Evolution, 13(1), 105–114.CrossRefGoogle ScholarPubMed
Muse, S. V. (1999). Modeling the molecular evolution of HIV sequences. In The Evolution of HIV, ed. Crandall, K. A., Chapter 4, pp. 122–152. Baltimore, MD: The Johns Hopkins University Press.Google Scholar
Muse, S. V. & Gaut, B. S. (1994). A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome. Molecular Biology and Evolution, 11, 715–724.Google ScholarPubMed
Myers, S. R. & Griffiths, R. C. (2003). Bounds on the minimum number of recombination events in a sample history. Genetics, 163, 375–394.Google Scholar
Needleman, S. B. & Wunsch, C. D. (1970). A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology, 48, 443–453.CrossRefGoogle ScholarPubMed
Negroni, M. & Buc, H. (2001). Mechanisms of retroviral recombination. Annual Reviews in Genetics, 35, 275–302.CrossRefGoogle ScholarPubMed
Nei, M. (1985). Molecular Evolutionary Genetics. New York: Columbia University Press.Google Scholar
Nei, M. & Gojobori, T. (1986). Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. Molecular Biology and Evolution, 3(5), 418–426.Google ScholarPubMed
Nei, M. & Kumar, S. (2000). Molecular Evolution and Phylogenetics. New York: Oxford University Press.Google Scholar
Nei, M., Kumar, S., & Takahashi, K. (1998). The optimization principle in phylogenetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small. Proceedings of the National Academy of Sciences, USA, 95, 12390–12397.CrossRefGoogle ScholarPubMed
Neuhauser, C. & Krone, S. M. (1997). The genealogy of samples in models with selection. Genetics, 145, 519–534.Google ScholarPubMed
Newton, M. A. & Raftery, A. E. (1994). Approximate Bayesian inference with the weighted likelihood bootstrap. Journal of the Royal Statistics Society Series B, 56, 3–48.Google Scholar
Nickle, D. C., Heath, L., Jensen, M. A.et al. (2007). HIV-specific probabilistic models of protein evolution. PLoS ONE, 2(6): e503. doi:10.1371/journal.pone.0000503.CrossRefGoogle ScholarPubMed
Nielsen, R. & Yang, Z. H. (1998). Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics, 148, 929–936.Google ScholarPubMed
Nielsen, R. & Yang, Z. (2003). Estimating the distribution of selection coefficients from phylogenetic data with applications to mitochondrial and viral DNA. Molecular Biology and Evolution, 20(8), 1231–1239.CrossRefGoogle ScholarPubMed
Nielsen, R., Williamson, S., Kim, Y., Hubisz, M. J., Clark, A. G., & Bustamante, C. (2005). Genomic scans for selective sweeps using SNP data. Genome Research, 15(11), 1566–1575.CrossRefGoogle ScholarPubMed
Nieselt-Struwe, K. & Haeseler, A. (2001). Quartet-mapping, a generalization of the likelihood-mapping procedure. Molecular Biology and Evolution, 18, 1204–1219.CrossRefGoogle ScholarPubMed
Ning, Z. A., Cox, J., & Mullikin, J. C. (2001). SSAHA: a fast search method for large DNA databases. Genome Research, 11, 1725–1729.CrossRefGoogle ScholarPubMed
Nixon, K. C. (1999). The parsimony ratchet, a new method for rapid parsimony analysis. Cladistics, 15, 407–414.CrossRefGoogle Scholar
Notredame, C. & Higgins, D. G. (1996). SAGA: Sequence alignment by genetic algorithm. Nucleic Acids Research, 24, 1515–1524.CrossRefGoogle ScholarPubMed
Notredame, C., Holm, L., & Higgins, D. G. (1998). COFFEE: an objective function for multiple sequence alignments. Bioinformatics, 14, 407–422.CrossRefGoogle ScholarPubMed
Notredame, C., Higgins, D. G., & Heringa, J. (2000). T-Coffee: a novel method for fast and accurate multiple sequence alignment. Journal of Molecular Biology, 302, 205–217.CrossRefGoogle ScholarPubMed
Nuin, P. A., Wang, Z., & Tillier, E. R. (2006). The accuracy of several multiple sequence alignment programs for proteins. Bioinformatics, 7, 471.Google ScholarPubMed
Nylander, J. A. A., Ronquist, F., Huelsenbeck, J. P., & Nieves-Aldrey, J. L. (2004). Bayesian phylogenetic analysis of combined data. Systematic Biology, 53, 47–67.CrossRefGoogle ScholarPubMed
O'Sullivan, O., Suhre, K., Abergel, C., Higgins, D. G., & Notredame, C. (2004). 3DCoffee: combining protein sequences and structures within multiple sequence alignments. Journal of Molecular Biology, 340(2), 385–395.CrossRefGoogle ScholarPubMed
Ochman, H. & Moran, N. A. (2001). Genes lost and genes found: evolution of bacterial pathogenesis and symbiosis. Science, 292, 1096–1099.CrossRefGoogle ScholarPubMed
Ochman, H., Lawrence, J. G., & Groisman, E. A. (2000). Lateral gene transfer and the nature of bacterial innovation. Nature, 405, 299–304.CrossRefGoogle ScholarPubMed
Ohta, T. (1973). Slightly deleterious mutant substitutions in evolution. Nature, 246, 96–98.CrossRefGoogle Scholar
Ohta, T. (1992). The nearly neutral theory of molecular evolution. Annual Review of Ecology and Systematics, 23, 263–286.CrossRefGoogle Scholar
Ohta, T. (2000). Mechanisms of molecular evolution. Philosophical Transactions Royal Society of London B Biological Sciences, 355(1403), 1623–1626.CrossRefGoogle ScholarPubMed
Ohta, T. (2002). Near-neutrality in evolution of genes and gene regulation. Proceedings of the National Academy of Sciences, USA, 99, 16134–16137.CrossRefGoogle ScholarPubMed
Ohta, T. & Gillespie, J. H. (1996). Development of neutral and nearly neutral theories. Theory of Population Biology, 49(2), 128–142.CrossRefGoogle ScholarPubMed
Olsen, G. J. (1987). Earliest phylogenetic branchings: Comparing rRNA-based evolutionary trees inferred with various techniques. Cold Spring Harbor Symposia on Quantitative Biology, LII, 825–837.CrossRefGoogle Scholar
Olsen, G. J., Matsuda, H., Hagstrom, R., & Overbeek, R. (1994). fastDNAml: a tool for construction of phylogenetic trees of DNA sequences using maximum likelihood. Computer Applications in the Biosciences, 10, 41–48.Google ScholarPubMed
Ota, S. & Li, W. H. (2000). NJML: a hybrid algorithm for the neighbor-joining and maximum-likelihood methods. Molecular Biology and Evolution, 17(9), 1401–1409.CrossRefGoogle ScholarPubMed
Page, R. D. M. & Holmes, E. C. (1998). Molecular Evolution: A Phylogenetic Approach. Oxford, UK: Blackwell Science.Google Scholar
Pagel, M. & Meade, A. (2004). A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data. Systematic Biology, 53(4), 571–581.CrossRefGoogle ScholarPubMed
Pamilo, P. & Bianchi, N. O. (1993). Evolution of the Zfx and Zfy genes: rates and interdependence between the genes. Molecular Biology and Evolution, 10(2), 271–281.Google ScholarPubMed
Papadopoulos, J. S. & Agarwala, R. (2007). COBALT: COnstraint Based ALignment Tool for Multiple Protein Sequences. Bioinformatics, 23, 1073–1079.CrossRefGoogle ScholarPubMed
Paraskevis, D., Lemey, P., Salemi, M., Suchard, M., Peer, Y., & Vandamme, A. M. (2003). Analysis of the evolutionary relationships of HIV-1 and SIVcpz sequences using Bayesian inference: implications for the origin of HIV-1. Molecular Biology and Evolution, 20, 1986–1996.CrossRefGoogle ScholarPubMed
Parida, L., Floratos, A., & Rigoutsos, I. I. (1998). MUSCA: an Algorithm for Constrained Alignment of Multiple Data Sequences. Genome Informatics Series Workshop Genome Information, 9, 112–119.Google ScholarPubMed
Pascarella, S. & Argos, P. (1992). Analysis of insertions deletions in protein structures. Journal of Molecular Biology, 224, 461–471.CrossRefGoogle ScholarPubMed
Patterson, C. (ed.) (1987). Molecules and Morphology in Evolution: Conflict or Compromise?Cambridge, UK: Cambridge University Press.
PAUP* 4.0 – Phylogenetic Analysis Using Parsimony (*and Other Methods): Sunderland, MA: Sinauer Associates.
Pearson, W. R. (1998). Empirical statistical estimates for sequence similarity searches. Journal of Molecular Biology, 276, 71–84.CrossRefGoogle ScholarPubMed
Pearson, W. R. & Lipman, D. J. (1988). Improved tools for biological sequence comparison. Proceedings of the National Academy of Sciences, USA, 85, 2444–2448.CrossRefGoogle ScholarPubMed
Pearson, W. R., Wood, T., Zhang, Z., & Miller, W. (1997). Comparison of DNA sequences with protein sequences. Genomics, 46, 24–36.CrossRefGoogle ScholarPubMed
Pearson, W. R., Robins, G., & Zhang, T. (1999). Generalized neighbor-joining: More reliable phylogenetic tree reconstruction. Molecular Biology and Evolution, 16, 806–816.CrossRefGoogle ScholarPubMed
Pei, J. & Grishin, N. V. (2006). MUMMALS: multiple sequence alignment improved by using hidden Markov models with local structural information. Nucleic Acids Research, 34(16), 4364–4374.CrossRefGoogle ScholarPubMed
Pei, J. & Grishin, N. V. (2007). PROMALS: towards accurate multiple sequence alignments of distantly related proteins. Bioinformatics, 23(7), 802–808.CrossRefGoogle ScholarPubMed
Pei, J., Sadreyev, R., & Grishin, N. V. (2003). PCMA: fast and accurate multiple sequence alignment based on profile consistency. Bioinformatics, 19(3), 427–428.CrossRefGoogle ScholarPubMed
Pfaffelhuber, P., Haubold, B., & Wakolbinger, A. (2006). Approximate genealogies under genetic hitchhiking. Genetics, 174, 1995–2008.CrossRefGoogle ScholarPubMed
Philippe, H. & Forterre, P. (1999). The rooting of the universal tree of life is not reliable. Journal of Molecular Evolution, 49, 509–523.CrossRefGoogle Scholar
Phuong, T. M., Do, C. B., Edgar, R. C., & Batzoglou, S. (2006). Multiple alignment of protein sequences with repeats and rearrangements. Nucleic Acids Research, 34(20), 5932–5942.CrossRefGoogle ScholarPubMed
Pillai, S. K., Kosakovsky Pond, S. L., Woelk, C. H., Richman, D. D., & Smith, D. M. (2005). Codon volatility does not reflect selective pressure on the HIV-1 genome. Virology, 336(2), 137–143.CrossRefGoogle Scholar
Plotkin, J. B. & Dushoff, J. (2003). Codon bias and frequency-dependent selection on the hemagglutinin epitopes of influenza A virus. Proceedings of the National Academy of Sciences, USA, 100(12), 7152–7157.CrossRefGoogle ScholarPubMed
Plotkin, J. B., Dushoff, J., & Fraser, H. B. (2004). Detecting selection using a single genome sequence of M. tuberculosis and P. falciparum. Nature, 428(6986), 942–945.CrossRefGoogle ScholarPubMed
Plotkin, J. B., Dushoff, J., Desai, M. M., & Fraser, H. B. (2006). Codon usage and selection on proteins. Journal of Molecular Evolution, 63(5), 635–653.CrossRefGoogle ScholarPubMed
Pluzhnikov, A. & Donnelly, P. (1996). Optimal sequencing strategies for surveying molecular genetic diversity. Genetics, 144, 1247–1262.Google ScholarPubMed
Pol, D. (2004). Empirical problems of the hierarchical likelihood ratio test for model selection. Systematic Biology, 53(6), 949–962.CrossRefGoogle ScholarPubMed
Posada, D. & Crandall, K. (2001). Intraspecific gene genealogies: trees grafting into networks. Trends in Ecology and Evolution, 16, 37–45.CrossRefGoogle ScholarPubMed
Posada, D. (2001). Unveiling the molecular clock in the presence of recombination. Molecular Biology of Evolution, 18(10), 1976–1978.CrossRefGoogle Scholar
Posada, D. (2002). Evaluation of methods for detecting recombination from DNA sequences: empirical data. Molecular Biology and Evolution, 19, 708–717.CrossRefGoogle ScholarPubMed
Posada, D. (2003). Using Modeltest and PAUP* to select a model of nucleotide substitution. In Current Protocols in Bioinformatics, ed. Baxevanis, A. D., Davison, D. B., Page, R. D. M.et al., pp. 6.5.1–6.5.14. Chichester, UK: John Wiley & Sons, Inc.Google Scholar
Posada, D. (2006). ModelTest Server: a web-based tool for the statistical selection of models of nucleotide substitution online. Nucleic Acids Research, 34, W700–W703.CrossRefGoogle ScholarPubMed
Posada, D. & Buckley, T. R. (2004). Model selection and model averaging in phylogenetics: advantages of Akaike Information Criterion and Bayesian approaches over likelihood ratio tests. Systematic Biology, 53(5), 793–808.CrossRefGoogle ScholarPubMed
Posada, D. & Crandall, K. A. (1998). Modeltest: testing the model of DNA substitution. Bioinformatics, 14(9), 817–818.CrossRefGoogle ScholarPubMed
Posada, D. & Crandall, K. A. (2001a). Evaluation of methods for detecting recombination from DNA sequences: computer simulations. Proceedings of the National Academy of Sciences, USA, 98, 13757–13762.CrossRefGoogle ScholarPubMed
Posada, D. & Crandall, K. A. (2001b). Intraspecific gene genealogies: trees grafting into networks. Trends in Ecology and Evolution, 16, 37–45.CrossRefGoogle ScholarPubMed
Posada, D. & Crandall, K. A. (2001c). Selecting the best-fit model of nucleotide substitution. Systematic Biology, 50(4), 580–601.CrossRefGoogle ScholarPubMed
Posada, D. & Crandall, K. A. (2002). The effect of recombination on the accuracy of phylogeny estimation. Journal of Molecular Evolution, 54, 396–402.CrossRefGoogle ScholarPubMed
Posada, D., Crandall, K. A., & Holmes, E. C. (2002). Recombination in evolutionary genomics. Annual Reviews in Genetics, 36, 75–97.CrossRefGoogle ScholarPubMed
Press, W. H., Flannery, B. P., Teukolsky, S. A., & Vetterling, W. T. (1992). Numerical Recipes in C: The Art of Scientific Computing, 2nd edn. Cambridge, UK: Cambridge University Press.Google Scholar
Przeworski, M., Coop, G., & Wall, J. D. (2005). The signature of positive selection on standing genetic variation. Evolution, 59, 2312–2323.CrossRefGoogle ScholarPubMed
Pybus, O. G. (2006). Model selection and the molecular clock. PLoS Biology, 4(5), e151.CrossRefGoogle ScholarPubMed
Pybus, O. G., Drummond, A. J., Nakano, T., Robertson, B. H., & Rambaut, A. (2003). The epidemiology and iatrogenic transmission of hepatitis C virus in Egypt: a Bayesian coalescent approach. Molecular Biology and Evolution, 20(3), 381–387.CrossRefGoogle ScholarPubMed
Pybus, O. G., Rambaut, A., Belshaw, R., Freckleton, R. P., Drummond, A. J., & Holmes, E. C. (2007). Phylogenetic evidence for deleterious mutation load in RNA viruses and its contribution to viral evolution. Molecular Biology and Evolution, 24(3), 845–852.CrossRefGoogle ScholarPubMed
Quenouille, M. H. (1956). Notes on bias in estimation. Biometrika, 43, 353–336.CrossRefGoogle Scholar
Raftery, A. E. (1996). Hypothesis testing and model selection. In Markov Chain Monte Carlo in Practice, ed. Gilks, W. R., Richardson, S., & Spiegelhalter, D. J., pp. 163–187. London; New York: Chapman & Hall.Google Scholar
Rambaut, A. (2000). Estimating the rate of molecular evolution: incorporating non-contemporaneous sequences into maximum likelihood phylogenies. Bioinformatics, 16(4), 395–399.CrossRefGoogle ScholarPubMed
Rambaut, A. & Bromham, L. (1998). Estimating divergence dates from molecular sequences. Molecular Biology of Evolution, 15(4), 442–448.CrossRefGoogle ScholarPubMed
Rambaut, A. & Drummond, A. J. (2003). TRACER: Available from http://evolve.zoo.ox. ac.uk/software/.
Rambaut, A. & Grassly, N. C. (1997). Seq-Gen: an application for the Monte Carlo simulation of DNA sequence evolution along phylogenetic trees. Computers Applications Biosciences, 13, 235–238.Google ScholarPubMed
Rand, D. M. & Kann, L. M. (1996). Excess amino acid polymorphism in mitochondrial DNA: contrasts among genes from Drosophila, mice, and humans. Molecular Biology and Evolution, 13(6), 735–748.CrossRefGoogle ScholarPubMed
Rannala, B. & Yang, Z. H. (2003). Bayes estimation of species divergence times and ancestral population sizes using DNA sequences from multiple loci. Genetics, 164(4), 1645– 1656.Google ScholarPubMed
Raphael, B., Zhi, D., Tang, H., & Pevzner, P. (2004). A novel method for multiple alignment of sequences with repeated and shuffled elements. Genome Research, 14(11), 2336–2346.CrossRefGoogle ScholarPubMed
Redelings, B. D. & Suchard, M. A. (2005). Joint Bayesian estimation of alignment and phylogeny. Systematic Biology, 54(3), 401–418.CrossRefGoogle ScholarPubMed
Regier, J. C. & Shultz, J. W. (1997). Molecular phylogeny of the major arthropod groups indicates polyphyly of crustaceans and a new hypothesis for the origin of hexapods. Molecular Biology and Evolution, 14, 902–913.CrossRefGoogle Scholar
Roberts, G. O. & Rosenthal, J. S. (1998). Optimal scaling of discrete approximations to Langevin diffusions. Journal of the Royal Statistical Society: Series B, 60, 255–268.CrossRefGoogle Scholar
Roberts, G. O. & Rosenthal, J. S. (2001). Optimal scaling for various Metropolis–Hastings algorithms. Statistical Science, 16, 351–367.CrossRefGoogle Scholar
Roberts, G. O. & Rosenthal, J. S. (2006). Examples of adaptive MCMC. Preprint available from http://www.probability.ca/jeff/ftpdir/adaptex.pdf.
Roberts, G. O., Gelman, A., & Gilks, W. R. (1997). Weak convergence and optimal scaling of random walk Metropolis algorithms. Annals of Applied Probability, 7, 110–120.Google Scholar
Robertson, D. L., Sharp, P. M., McCutchan, F. E., & Hahn, B. H. (1995). Recombination in HIV-1. Nature, 374, 124–126.CrossRefGoogle ScholarPubMed
Robinson, D. M., Jones, D. T., Kishino, H., Goldman, N., & Thorne, J. L. (2003). Protein evolution with dependence among codons due to tertiary structure. Molecular Biology and Evolution, 20(10), 1692–1704.CrossRefGoogle ScholarPubMed
Robinson, M., Gouy, M., Gautier, C., & Mouchiroud, D. (1998). Sensitivity of the relative-rate test to taxonomic sampling. Molecular Biology of Evolution, 15(9), 1091–1098.CrossRefGoogle ScholarPubMed
Rodríguez, F., Oliver, J. F., Marín, A., & Medina, J. R. (1990). The general stochastic model of nucleotide substitution. Journal of Theoretical Biology, 142, 485–501.CrossRefGoogle ScholarPubMed
Rodrigo, A. G. & Felsenstein, J. (1999). Coalescent approaches to HIV population genetics. In The Evolution of HIV, ed. Crandall, K. A.. Baltimore, MD: Johns Hopkins University Press.Google ScholarPubMed
Rodrigo, A. G., Shaper, E. G., Delwart, E. L.et al. (1999). Coalescent estimates of HIV-1 generation time in vivo. Proceedings of the National Academy of Sciences, USA, 96, 2187–2191.CrossRefGoogle ScholarPubMed
Rodrigue, N., Lartillot, N., Bryant, D., & Philippe, H. E. (2005). Site interdependence attributed to tertiary structure in amino acid sequence evolution. Gene, 347(2), 207–217.CrossRefGoogle ScholarPubMed
Rodriguez, F., Oliver, J. L., Marin, A., & Medina, J. R. (1990). The general stochastic model of nucleotide substitution. Journal of Theoretical Biology, 142, 485–501.CrossRefGoogle ScholarPubMed
Rogers, J. S. (1997). On the consistency of maximum likelihood estimation of phylogenetic trees from nucleotide sequences. Systems in Biology, 46(2), 354–357.CrossRefGoogle ScholarPubMed
Ronquist, F. & Huelsenbeck, J. P. (2003). MRBAYES 3: Bayesian phylogenetic inference under mixed models. Bioinformatics, 19, 1572–1574.CrossRefGoogle ScholarPubMed
Rosenberg, N. A. & Nordborg, M. (2002). Genealogical trees, coalescent theory, and the analysis of genetic polymorphisms. Nature Reviews Genetics, 3, 380–390.CrossRefGoogle ScholarPubMed
Roshan, U. & Livesay, D. R. (2006). Probalign: multiple sequence alignment using partition function posterior probabilities. Bioinformatics, 22(22), 2715–2721.CrossRefGoogle ScholarPubMed
Rousseau, C. M., Learn, G. H., Bhattacharya, T.et al. (2007). Extensive intrasubtype recombination in South African human immunodeficiency virus type 1 subtype C infections. Journal of Virology, 81, 4492–4500.CrossRefGoogle ScholarPubMed
Russo, C. A. M., Takezaki, N., & Nei, M. (1996). Efficiencies of different genes and different tree-building methods in recovering a known vertebrate phylogeny. Molecular Biology and Evolution, 13, 525–536.CrossRefGoogle ScholarPubMed
Rzhetsky, A. & Nei, M. (1992). A simple method for estimating and testing minimum-evolution trees. Molecular Biology and Evolution, 9, 945–967.Google Scholar
Rzhetsky, A. & Nei, M. (1993). Theoretical foundation of the minimum-evolution method of phylogenetic inference. Molecular Biology and Evolution, 10, 1073–1095.Google ScholarPubMed
Sabeti, P. C., Reich, D. E., Higgins, J. M.et al. (2002). Detecting recent positive selection in the human genome from haplotype structure. Nature, 419(6909), 832–837.CrossRefGoogle ScholarPubMed
Sabeti, P. C., Schaffner, S. F., Fry, B.et al. (2006). Positive natural selection in the human lineage. Science, 312(5780), 1614–1620.CrossRefGoogle ScholarPubMed
Saitou, N. & Nei, M. (1987). The neighbor-joining method: a new method for reconstructing phylogenetic trees. Molecular Biology and Evolution, 4(4), 406–425.Google ScholarPubMed
Saitou, N. & Imanishi, T. (1989). Relative efficiencies of the Fitch–Margoliash, maximum-parsimony, maximum-likelihood, minimum-evolution, and neighbor-joining methods of phylogenetic tree construction in obtaining the correct tree. Molecular Biology and Evolution, 6, 514–525.Google Scholar
Salemi, M., Desmyter, J., & Vandamme, A. M. (2000). Tempo and mode of human and simian T-lymphotropic virus (HTLV/STLV) evolution revealed by analyses of full-genome sequences. Molecular Biology and Evolution, 17, 374–386.CrossRefGoogle ScholarPubMed
Salemi, M., Strimmer, K., Hall, W. W.et al. (2001). Dating the common ancestor of SIVcpz and HIV-1 group M and the origin of HIV-1 subtypes using a new method to uncover clock-like molecular evolution. FASEB Journal, 15, 267–268.CrossRefGoogle Scholar
Salter, L. A. & Pearl, D. K. (2001) Stochastic search strategy for estimation of maximum likelihood phylogenetic trees. Systematic Biology, 50, 7–17.CrossRefGoogle ScholarPubMed
Sanderson, M. J. (2002). Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach. Molecular Biology and Evolution, 19, 101–109.CrossRefGoogle ScholarPubMed
Sanjuán, R., Moya, A., & Elena, S. F. (2004). The distribution of fitness effects caused by single-nucleotide substitutions in an RNA virus. Proceedings of the National Academy of Sciences, USA, 101, 8396–8401.CrossRefGoogle Scholar
Sanjuan, R., Cuevas, J. M., Moya, A., & Elena, S. F. (2005). Epistasis and the adaptability of an RNA virus. Genetics, 170(3), 1001–1008.CrossRefGoogle ScholarPubMed
Sankoff, D. & Rousseau, P. (1975). Locating the vertixes of a Steiner tree in an arbitrary metric space. Mathematic Progress, 9, 240–276.CrossRefGoogle Scholar
Sankoff, D. (1985). Simultaneous solution of the RNA folding, alignment and protosequence problems. SIAM Journal on Applied Mathematics, 45, 810–825.CrossRefGoogle Scholar
Sawyer, S. (1989). Statistical tests for detecting gene conversion. Molecular Biology and Evolution, 6, 526–538.Google ScholarPubMed
Sawyer, S. A. & Hartl, D. L. (1992). Population genetics of polymorphism and divergence. Genetics, 132(4), 1161–1176.Google ScholarPubMed
Sawyer, S. L., Wu, L. I., Emerman, M., & Malik, H. S. (2005). Positive selection of primate TRIM5alpha identifies a critical species-specific retroviral restriction domain. Proceedings of the National Academy of Sciences, USA, 102(8), 2832–7.CrossRefGoogle ScholarPubMed
Schaffer, A. A., Aravind, L., Madden, T. L.et al. (2001). Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements. Nucleic Acids Research, 29, 2994–3005.CrossRefGoogle ScholarPubMed
Scheffler, K., Martin, D. P., & Seoighe, C. (2006). Robust inference of positive selection from recombining coding sequences. Bioinformatics, 22, 2493–2499.CrossRefGoogle ScholarPubMed
Schierup, M. H. & Hein, J. (2000a). Consequences of recombination on traditional phylogenetic analysis. Genetics, 156, 879–891.Google ScholarPubMed
Schierup, M. H. & Hein, J. (2000b). Recombination and the molecular clock. Molecular Biology and Evolution, 17, 1578–1579.CrossRefGoogle ScholarPubMed
Schmidt, H. A., Strimmer, K., Vingron, M., & Haeseler, A. (2002). TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing. Bioinformatics, 18(3), 502–504.CrossRefGoogle ScholarPubMed
Schuler, G. D., Altschul, S. F., & Lipman, D. J. (1991). A workbench for multiple alignment construction and analysis. Proteins, 9(3), 180–190.CrossRefGoogle ScholarPubMed
Schultz, A. K., Zhang, M., Leitner, T.et al. (2006). A jumping profile Hidden Markov Model and applications to recombination sites in HIV and HCV genomes. BMC Bioinformatics, 7, 265.CrossRefGoogle ScholarPubMed
Schwartz, A. S. & Pachter, L. (2007). Multiple alignment by sequence annealing. Bioinformatics, 23(2), e24–e29.CrossRefGoogle ScholarPubMed
Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464.CrossRefGoogle Scholar
Self, S. G. & Liang, K.-Y. (1987). Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions. Journal of the American Statistical Association, 82(398), 605–610.CrossRefGoogle Scholar
Seo, T. K., Kishino, H., & Thorne, J. L. (2004). Estimating absolute rates of synonymous and nonsynonymous nucleotide substitution in order to characterize natural selection and date species divergences. Molecular Biology of Evolution, 21(7), 1201–1213.CrossRefGoogle ScholarPubMed
Shapiro, B., Drummond, A. J., Rambaut, A.et al. (2004). Rise and fall of the Beringian steppe bison. Science, 306(5701), 1561–1565.CrossRefGoogle ScholarPubMed
Sharp, P. M. (1997). In search of molecular Darwinism. Nature, 385(6612), 111–112.Google ScholarPubMed
Shimodaira, H. (2002). An approximately unbiased test of phylogenetic tree selection. Systematic Biology, 51, 492–508.CrossRefGoogle ScholarPubMed
Shimodaira, H. & Hasegawa, M. (1999). Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Molecular Biology and Evolution, 16, 1114–1116.CrossRefGoogle Scholar
Shimodaira, H. & Hasegawa, M. (2001). CONSEL: for assessing the confidence of phylogenetic tree selection. Bioinformatics, 17, 1246–1247.CrossRefGoogle ScholarPubMed
Shriner, D., Nickle, D. C., Jensen, M. A., & Mullins, J. I. (2003). Potential impact of recombination on sitewise approaches for detecting positive natural selection. Genetics Research, 81, 115–121.CrossRefGoogle ScholarPubMed
Siegel, S. & Castellan Jr, N. J. (1988). Nonparametric Statistics for the Behavioral Sciences. 2nd edn. New York: McGraw-Hill.Google Scholar
Siepel, A. C., Halpern, A. L., Macken, C., & Korber, B. T. (1995). A computer program designed to screen rapidly for HIV type 1 intersubtype recombinant sequences. AIDS Research Human Retroviruses, 11, 1413–1416.CrossRefGoogle ScholarPubMed
Siguroardottir, S., Helgason, A., Gulchar, J. R., Stefansson, K., & Donnelly, P. (2000). The mutation rate in the human mtDNA control region. American Journal of Human Genetics, 66, 1599–1609.CrossRefGoogle Scholar
Sikes, D. S. & Lewis, P. O. (2001). Beta Software, Version 1. PAUPRat: PAUP* Implementation of the Parsimony Ratchet. Distributed by the authors. Storrs: University of Connecticut, Department of Ecology and Evolutionary Biology. (http://viceroy.eeb.uconn.edu/paupratweb/pauprat.htm).Google Scholar
Silva, A. E., Villanueva, W. J., Knidel, H., Bonato, V. C., Reis, S. F., & Zuben, F. J. (2005). A multi-neighbor-joining approach for phylogenetic tree reconstruction and visualization. Genetics and Molecular Research, 4(3), 525–534.Google ScholarPubMed
Simmonds, P. & Welch, J. (2006). Frequency and dynamics of recombination within different species of human enteroviruses. Journal of Virology, 80, 483–493.CrossRefGoogle ScholarPubMed
Simmonds, P., Zhang, L. Q., McOmish, F., Balfe, P., Ludlam, C. A., & Brown, A. J. L. (1991). Discontinuous sequence change of human-immunodeficiency-virus (HIV) type-1 env sequences in plasma viral and lymphocyte-associated proviral populations in vivo – implications for models of HIV pathogenesis. Journal of Virology, 65(11), 6266–6276.Google ScholarPubMed
Simossis, V. A. & Heringa, J. (2005). PRALINE: a multiple sequence alignment toolbox that integrates homology-extended and secondary structure information. Nucleic Acids Research, 33(Web Server issue), W289–W294.CrossRefGoogle ScholarPubMed
Sjödin, P., Kaj, I., Krone, S., Lascoux, M., & Nordborg, M. (2005). On the meaning and existence of an effective population size. Genetics, 169, 1061–1070.CrossRefGoogle ScholarPubMed
Smith, J. M. (1999). The detection and measurement of recombination from sequence data. Genetics, 153, 1021–1027.Google ScholarPubMed
Smith, N. G. & Eyre-Walker, A. (2002). Adaptive protein evolution in Drosophila. Nature, 415(6875), 1022–1024.CrossRefGoogle ScholarPubMed
Smith, R. F. & Smith, T. F. (1992). Pattern-induced multi-sequence alignment (PIMA) algorithm employing secondary structure-dependent gap penalties for use in comparative protein modelling. Protein Engineering, 5(1), 35–41.CrossRefGoogle ScholarPubMed
Smith, T. F & Waterman, M. S. (1981). Identification of common molecular subsequences. Journal of Molecular Biology, 147, 195–197.CrossRefGoogle ScholarPubMed
Sneath, P. H. (1998). The effect of evenly spaced constant sites on the distribution of the random division of a molecular sequence. Bioinformatics, 14, 608–616.CrossRefGoogle ScholarPubMed
Sneath, P. H. A. & Sokal, R. R. (1973). Numerical Taxonomy. San Francisco: W. H. Freeman.Google Scholar
Sokal, R. R. & Michener, C. D. (1958). A statistical method for evaluating systematic relationships. University of Kansas Science Bulletin, 38, 1409–1438.Google Scholar
Sorhannus, U. & Kosakovsky Pond, S. L. (2006). Evidence for positive selection on a sexual reproduction gene in the diatom genus Thalassiosira (Bacillariophyta). Journal of Molecular Evolution, 63, 231–239.CrossRefGoogle Scholar
Sourdis, J. & Krimbas, C. (1987). Accuracy of phylogenetic trees estimated from DNA sequence data. Molecular Biology and Evolution, 4, 159–166.Google ScholarPubMed
Stamatakis, A. (2005). An efficient program for phylogenetic inference using simulated annealing. In Online Proceedings of the 4th IEEE International Workshop on High Performance Computational Biology (HICOMB 2005), p. 8, Denver.Google Scholar
Stamatakis, A. (2006). RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics, 22, 2688–2690.CrossRefGoogle ScholarPubMed
Stamatakis, A. P., Ludwig, T., & Meier, H. (2005). RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees. Bioinformatics, 21, 456–463.CrossRefGoogle ScholarPubMed
Steel, M. (1994). Recovering a tree from the Markov leaf colourations it generates under a Markov model. Applied Mathematics Letters, 7, 19–23.CrossRefGoogle Scholar
Steel, M. & Penny, D. (2000). Parsimony, likelihood, and the role of models in molecular phylogenetics. Molecular Biology and Evolution, 17, 839–850.CrossRefGoogle ScholarPubMed
Steel, M. A., Lockhart, P. J., & Penny, D. (1993). Confidence in evolutionary trees from biological sequence data. Nature, 364, 440–442.CrossRefGoogle ScholarPubMed
Steel, M., Lockhart, P. J., & Penny, D. (1995). A frequency-dependent significance test for parsimony. Molecular Phylogenetics and Evolution, 4, 64–71.CrossRefGoogle ScholarPubMed
Stern, A. & Pupko, T. (2006). An evolutionary space-time model with varying among-site dependencies. Molecular Biology and Evolution, 23(2), 392–400.CrossRefGoogle ScholarPubMed
Stewart, C. A., Hart, D., Berry, D. K., Olsen, G. J., Wernert, E. A., & Fischer, W. (2001). Parallel implementation and performance of fastDNAml – a program for maximum likelihood phylogenetic inference. In Proceedings of the International Conference on High Performance Computing and Communications – SC2001, pp. 191–201.
Stoye, J. (1998). Multiple sequence alignment with the Divide-and-Conquer method. Gene, 211(2), GC45–GC56.CrossRefGoogle ScholarPubMed
Stoye, J., Moulton, V., & Dress, A. W. (1997). DCA: an efficient implementation of the divide-and-conquer approach to simultaneous multiple sequence alignment. Computer Applications in the Biosciences, 13, 625–626.Google ScholarPubMed
Stremlau, M., Owens, C. M., Perron, M. J., Kiessling, M., Autissier, P., & Sodroski, J. (2004). The cytoplasmic body component TRIM5alpha restricts HIV-1 infection in Old World monkeys. Nature, 427(6977), 848–853.CrossRefGoogle ScholarPubMed
Strimmer, K. & Moulton, V. (2000). Likelihood analysis of phylogenetic networks using directed graphical models. Molecular Biology and Evolution, 17, 875–881.CrossRefGoogle ScholarPubMed
Strimmer, K. & Rambaut, A. (2002). Inferring confidence sets of possibly misspecified gene trees. Proceedings of the Royal Society of London B, 269, 137–142.CrossRefGoogle ScholarPubMed
Strimmer, K. & Haeseler, A. (1996). Quartet-puzzling: a quartet maximum-likelihood method for reconstructing tree topologies. Molecular Biology and Evolution, 13, 964–969.CrossRefGoogle Scholar
Strimmer, K. & Haeseler, A. (1997). Likelihood-mapping: a simple method to visualize phylogenetic content of a sequence alignment. Proceedings of the National Academy of Sciences, USA, 94, 6815–6819.CrossRefGoogle ScholarPubMed
Strimmer, K. & Haeseler, A. (2003). Phylogeny inference based on maximum likelihood methods with tree-puzzle. In The Phylogenetic Handbook, ed. Salemi, M. & Vandamme, A.-M., pp. 137–159, Cambridge, UK: Cambridge University Press.Google Scholar
Strimmer, K., Forslund, K., Holland, B., & Moulton, V. (2003). A novel exploratory method for visual recombination detection. Genome Biology, 4, R33.CrossRefGoogle ScholarPubMed
Strimmer, K., Goldman, N., & Haeseler, A. (1997) Bayesian probabilities and quartet puzzling. Molecular Biology and Evolution, 14, 210–213.CrossRefGoogle Scholar
Studier, J. A. & Keppler, K. J. (1988). A note on the neighbor-joining algorithm of Saitou and Nei. Molecular Biology and Evolution, 5, 729–731.Google ScholarPubMed
Stumpf, M. P. & McVean, G. A. (2003). Estimating recombination rates from population-genetic data. Nature Review Genetics, 4, 959–968.CrossRefGoogle ScholarPubMed
Suarez, D. L., Senne, D. A., Banks, J.et al. (2004). Recombination resulting in virulence shift in avian influenza outbreak, Chile. Emergency Infections Diseases, 10, 693–699.CrossRefGoogle Scholar
Subramanian, A. R., Weyer-Menkhoff, J., Kaufmann, M., & Morgenstern, B. (2005). DIALIGN-T: an improved algorithm for segment-based multiple sequence alignment. BMC Bioinformatics, 6, 66.CrossRefGoogle ScholarPubMed
Suchard, M. A. & Redelings, B. D. (2006). BALI-PHY: simultaneous Bayesian inference of alignment and phylogeny. Bioinformatics, 22, 2047–2048.CrossRefGoogle ScholarPubMed
Suchard, M. A., Weiss, R. E., Dorman, K. S., & Sinsheimer, J. S. (2002). Oh brother, where art thou? A Bayes factor test for recombination with uncertain heritage. Systems in Biology, 51, 715–728.CrossRefGoogle ScholarPubMed
Sullivan, J. & Joyce, P. (2005). Model selection in phylogenetics. Annual Review of Ecology, Evolution and Systematics, 36, 445–466.CrossRefGoogle Scholar
Sullivan, J. & Swofford, D. L. (2001). Should we use model-based methods for phylogenetic inference when we know that assumptions about among-site rate variation and nucleotide substitution process are violated? Systematic Biology, 50, 723–729.CrossRefGoogle Scholar
Sullivan, J., Holsinger, K. E., & Simon, C. (1996). The effect of topology on estimates of among-site rate variation. Journal of Molecular Evolution, 42, 308–312.CrossRefGoogle ScholarPubMed
Sullivan, J., Abdo, Z., Joyce, P., & Swofford, D. L. (2005). Evaluating the performance of a successive-approximations approach to parameter optimization in maximum-likelihood phylogeny estimation. Molecular Biology and Evolution, 22, 1386–1392.CrossRefGoogle ScholarPubMed
Suzuki, Y. & Gojobori, T. (1999). A method for detecting positive selection at single amino acid sites. Molecular Biology and Evolution, 16, 1315–1328.CrossRefGoogle ScholarPubMed
Suzuki, Y. & Nei, M. (2004). False-positive selection identified by ML-based methods: examples from the sig1 gene of the diatom Thalassiosira weissflogii and the tax gene of a human T-cell lymphotropic virus. Molecular Biology and Evolution, 21, 914–921.CrossRefGoogle ScholarPubMed
Suzuki, Y., Gojobori, T., & Nei, M. (2001). ADAPTSITE: detecting natural selection at single amino acid sites. Bioinformatics, 17, 660–661.CrossRefGoogle ScholarPubMed
Swanson, W. J., Nielsen, R., & Yang, Q. (2003). Pervasive adaptive evolution in mammalian fertilization proteins. Molecular Biology and Evolution, 20(1), 18–20.CrossRefGoogle ScholarPubMed
Swofford, D. (1993) PAUP (Phylogenetic Analysis Using Parsimony). Smithsonian Institution, Washington, Version 4.0beta, MA: Sinauer Associates of Sunderland.Google Scholar
Swofford, D. L. (2002). PAUP*. Phylogenetic Analysis Using Parsimony (* and other methods). Version 4.0b10. Sunderland, MA (USA): Sinauer Associates, Inc.Google Scholar
Swofford, D. L. & Maddison, W. P. (1987). Reconstructing ancestral character states under Wagner parsimony. Mathematical Biosciences, 87, 199–229.CrossRefGoogle Scholar
Swofford, D. L., Olsen, G. J., Waddell, P. J., & Hillis, D. M. (1996). Phylogenetic inference. In Molecular Systematics, 2nd edn., ed. Hillis, D. M., Moritz, C., & Mable, B. K., pp. 407–514. Sunderland, Massachusetts, USA: Sinauer Associates, Inc.Google Scholar
Swofford, D. L. (1998). PAUP*. Phylogenetic Analysis Using Parsimony (* and other methods). Version 4. Sunderland, MA: Sinauer Associates.Google Scholar
Sze, S. H., Lu, Y., & Yang, Q. (2006). A polynomial time solvable formulation of multiple sequence alignment. Journal of Computer Biology, 13(2), 309–319.CrossRefGoogle ScholarPubMed
Tajima, F. (1989). Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics, 123(3), 585–595.Google ScholarPubMed
Takezaki, N., Rzhetsky, A., & Nei, M. (1995). Phylogenetic test of the molecular clock and linearized trees. Molecular Biology of Evolution, 12(5), 823–833.Google ScholarPubMed
Tamura, K. & Nei, M. (1993). Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Molecular Biology and Evolution, 10, 512–526.Google ScholarPubMed
Tavaré, S. (1986). Some probabilistic and statistical problems in the analysis of DNA sequences. Lectures in Mathematics and Life Sciences, 17, 57–86.Google Scholar
Templeton, A., Crandall, K., & Sing, C. (1992). A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data. III. Cladogram estimation, Genetics, 132, 619–633.Google ScholarPubMed
Thompson, J. D., Higgins, D. G., & 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 Research, 22, 4673–4680.CrossRefGoogle ScholarPubMed
Thompson, J. D., Gibson, T. J., Plewniak, F., Jeanmougin, F., & Higgins, D. G. (1997). The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Research, 25, 4876–4882.CrossRefGoogle ScholarPubMed
Thompson, J. D., Plewniak, F., & Poch, O. (1999a). A comprehensive comparison of multiple sequence alignment programs. Nucleic Acids Research, 27, 2682–2690.CrossRefGoogle ScholarPubMed
Thompson, J. D., Plewniak, F., & Poch, O. (1999b). BaliBase: a benchmark alignment database for the evaluation of multiple alignment programs. Bioinformatics, 15, 87–88.CrossRefGoogle ScholarPubMed
Thompson, W. W., Shay, D. K., Weintraub, E.et al. (2003). Mortality associated with influenza and respiratory syncytial virus in the united states. Journal of the American Medical Association, 289, 179–186.CrossRefGoogle ScholarPubMed
Thomson, R., Pritchard, J. K., Shen, P., Oefner, P. J., & Feldman, M. W. (2000). Recent common ancestry of human Y chromosomes: Evidence from DNA sequence data. Proceedings of the National Academy of Science, USA, 97(13), 7360–7365.CrossRefGoogle ScholarPubMed
Thorne, J. L. & Kishino, H. (2002). Divergence time and evolutionary rate estimation with multilocus data. Systematic Biology, 51(5), 689–702.CrossRefGoogle ScholarPubMed
Thorne, J. L., Kishino, H., & Felsenstein, J. (1992). Inching toward reality: an improved likelihood model of sequence evolution. Journal of Molecular Evolution, 34, 3–16.CrossRefGoogle ScholarPubMed
Thorne, J. L., Kishino, H., & Painter, I. S. (1998). Estimating the rate of evolution of the rate of molecular evolution. Molecular Biology of Evolution, 15(12), 1647–1657.CrossRefGoogle ScholarPubMed
Thorne, J. L., Kishino, H., & Felsenstein, J. (1991). An evolutionary model for maximum likelihood alignment of DNA sequences. Journal of Molecular Evolution, 33, 114–124.CrossRefGoogle ScholarPubMed
Tishkoff, S. A., Reed, F. A., Ranciaro, A.et al. (2007). Convergent adaptation of human lactase persistence in Africa and Europe. Nature Genetics, 39(1), 31–40.CrossRefGoogle ScholarPubMed
Toomajian, C. & Kreitman, M. (2002). Sequence variation and haplotype structure at the human HFE locus. Genetics, 161(4), 1609–1623.Google ScholarPubMed
Tuffley, C. & Steel, M. (1997). Links between maximum likelihood and maximum parsimony under a simple model of site substitution. Bulletin of Mathematical Biology, 59, 581–607.CrossRefGoogle Scholar
Tuplin, A., Wood, J., Evans, D. J., Patel, A. H., & Simmonds, P. (2002). Thermodynamic and phylogenetic prediction of RNA secondary structures in the coding region of hepatitis C virus. RNA, 8, 824–841.CrossRefGoogle ScholarPubMed
Tzeng, Y.-H., Pan, R., & Li, W.-H. (2004). Comparison of three methods for estimating rates of synonymous and nonsynonymous nucleotide substitutions. Molecular Biology and Evolution, 21(12), 2290–2298.CrossRefGoogle ScholarPubMed
Uzzel, T. & Corbin, K. W. (1971). Fitting discrete probability distributions to evolutionary events. Sciences, 172, 1089–1096.CrossRefGoogle Scholar
Cuyck, H., Fan, J., Robertson, D. L., & Roques, P. (2005). Evidence of recombination between divergent hepatitis E viruses. Journal of Virology, 79, 9306–9314.CrossRefGoogle ScholarPubMed
Peer, Y. & Wachter, R. (1994). TREECON for Windows: A software package for the construction and drawing of evolutionary trees for the Microsoft Windows environment. Computer Applications in the Biosciences, 10, 569–570.Google ScholarPubMed
Peer, Y., Rijk, P., Wuyts, J., Winkelmans, T., & Wachter, R. (2000a). The European small subunit ribosomal RNA database. Nucleic Acids Research, 28, 175–176.CrossRefGoogle ScholarPubMed
Peer, Y., Rensing, S., Maier, U.-G., & Wachter, R. (1996). Substitution rate calibration of small ribosomal subunit RNA identifies chlorarachniophyte endosymbionts as remnants of green algae. Proceedings of the National Academy of Sciences, USA, 93, 7732–7736.CrossRefGoogle ScholarPubMed
Peer, Y., Baldauf, S., Doolittle, W. F., & Meyer, A. (2000b). An updated and comprehensive rRNA phylogeny of crown eukaryotes based on rate-calibrated evolutionary distances. Journal of Molecular Evolution, 51, 565–576.CrossRefGoogle ScholarPubMed
Walle, I., Lasters, I., & Wyns, L. (2004). Align-m – a new algorithm for multiple alignment of highly divergent sequences. Bioinformatics, 20(9), 1428–1435.CrossRefGoogle ScholarPubMed
Walle, I., Lasters, I., & Wyns, L. (2005). SABmark – a benchmark for sequence alignment that covers the entire known fold space. Bioinformatics, 21(7), 1267–1268.CrossRefGoogle ScholarPubMed
Vennema, H., Poland, A., Foley, J., & Pedersen, N. C. (1998). Feline infectious peritonitis viruses arise by mutation from endemic feline enteric coronaviruses. Virology, 243, 150–157.CrossRefGoogle ScholarPubMed
Vigilant, L., Stoneking, M., Harpending, H., Hawkes, K., & Wilson, A. C. (1991). African populations and the evolution of human mitochondrial DNA. Science, 253(5027), 1503–1507.CrossRefGoogle ScholarPubMed
Vinh, L. S. & Haeseler, A. (2004). IQPNNI: Moving fast through tree space and stopping in time. Molecular Biology and Evolution, 21, 1565–1571.CrossRefGoogle Scholar
Voight, B. F., Kudaravalli, S., Wen, X., & Pritchard, J. K. (2006). A map of recent positive selection in the human genome. PLoS Biology, 4(3), e72.CrossRefGoogle ScholarPubMed
Wakeley, J. (1993). Substitution rate variation among sites in hypervariable region 1 of human mitochondrial DNA. Journal of Molecular Evolution, 37, 613–623.CrossRefGoogle ScholarPubMed
Walldorf, U. & Hovemann, B. T. (1990). Apis mellifera cytoplasmic elongation factor 1α (EF-1α) is closely related to Drosophila melanogaster EF-1α. FEBS, 267, 245–249.CrossRefGoogle Scholar
Ward, R. H., Frazer, B. L., Dew-Jager, K., & Pääbo, S. (1991). Extensive mitochondrial diversity within a single Amerindian tribe. Proceedings of the National Academy of Sciences, USA, 88, 8720–8724.CrossRefGoogle ScholarPubMed
Wasserman, L. (2000). Bayesian model selection and model averaging. Journal Mathematical Psychology, 44(1), 92–107.CrossRefGoogle ScholarPubMed
Watterson, G. A. (1975). On the number of segregating sites in genetical models without recombination. Theoretical Population Biology, 7, 256–276.CrossRefGoogle ScholarPubMed
Webster, R. G., Laver, W. G., Air, W. G., & Schild, G. C. (1982). Molecular mechanisms of variation in influenza viruses. Nature, 296(5853), 115–121.CrossRefGoogle ScholarPubMed
Webster, R. G., Bean, W. J., Gorman, O. T., Chambers, T. M., & Kawaoka, Y. (1992). Evolution and ecology of influenza A viruses. Microbiology Reviews, 56, 152–179.Google ScholarPubMed
Wei, X. P., Decker, J. M., Wang, S. Y.et al. (2003). Antibody neutralization and escape by HIV-1. Nature, 422(6929), 307–312.CrossRefGoogle ScholarPubMed
Weiller, G. F. (1998). Phylogenetic profiles: a graphical method for detecting genetic recombinations in homologous sequences. Molecular Biology and Evolution, 15, 326–335.CrossRefGoogle ScholarPubMed
Wernersson, R. & Pedersen, A. G. (2003). RevTrans: multiple alignment of coding DNA from aligned amino acid sequences. Nucleic Acids Research, 31(13), 3537–3539.CrossRefGoogle ScholarPubMed
Westfall, P. H. & Young, S. S. (1993). Resampling-based Multiple Testing: Examples and Methods for P-value Adjustment. New York, USA: John Wiley and Sons.Google Scholar
Whelan, S. & Goldman, N. (1999). Distributions of statistics used for the comparison of models of sequence evolution in phylogenetics. Molecular Biology and Evolution, 16(9), 1292–1299.CrossRefGoogle Scholar
Whelan, S. & Goldman, N. (2001). A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach. Molecular Biology and Evolution, 18(5), 691–699.CrossRefGoogle ScholarPubMed
Whelan, S. & Goldman, N. (2004). Estimating the frequency of events that cause multiple-nucleotide changes. Genetics, 167, 2027–2043.CrossRefGoogle Scholar
Williamson, S. (2003). Adaptation in the env gene of HIV-1 and evolutionary theories of disease progression. Molecular Biology and Evolution, 20(8), 1318–1325.CrossRefGoogle Scholar
Williamson, S. & Orive, M. E. (2002). The genealogy of a sequence subjected to purifying selection at multiple sites. Molecular Biology and Evolution, 19, 1376–1384.CrossRefGoogle Scholar
Williamson, S., Fledel-Alon, A., & Bustamante, C. D. (2004). Population genetics of polymorphism and divergence for diploid selection models with arbitrary dominance. Genetics, 168(1), 463–475.CrossRefGoogle ScholarPubMed
Wilson, D. J. & McVean, G. (2006). Estimating diversifying selection and functional constraint in the presence of recombination. Genetics, 172, 1411–1425.CrossRefGoogle Scholar
Wilson, I. J., Weale, M. E., & Balding, D. J. (2003). Inferences from DNA data: population histories, evolutionary processes and forensic match probabilities. Journal of the Royal Statistics Society A–Statistics in Society, 166, 155–188.CrossRefGoogle Scholar
Wiuf, C. & Posada, D. (2003). A coalescent model of recombination hotspots. Genetics, 164, 407–417.Google ScholarPubMed
Wiuf, C., Christensen, T., & Hein, J. (2001). A simulation study of the reliability of recombination detection methods. Molecular Biology and Evolution, 18, 1929–1939.CrossRefGoogle ScholarPubMed
Wolfe, K. H., Li, W. H., & Sharp, P. M. (1987). Rates of nucleotide substitution vary greatly among plant mitochondrial, chloroplast, and nuclear DNAs. Proceedings of the National Academy of Sciences, USA, 84(24), 9054–9058.CrossRefGoogle ScholarPubMed
Wong, W. S. & Nielsen, R. (2004). Detecting selection in noncoding regions of nucleotide sequences. Genetics, 167(2), 949–958.CrossRefGoogle ScholarPubMed
Wong, W. S., Yang, Z., Goldman, N., & Nielsen, R. (2004). Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequences and for identifying positively selected sites. Genetics, 168(2), 1041–1051.CrossRefGoogle ScholarPubMed
Wootton, J. C. & Federhen, S. (1993). Statistics of local complexity in amino acid sequences and sequence databases. Computers and Chemistry, 17, 149–163.CrossRefGoogle Scholar
Worobey, M. (2001). A novel approach to detecting and measuring recombination: new insights into evolution in viruses, bacteria, and mitochondria. Molecular Biology and Evolution, 18, 1425–1434.CrossRefGoogle ScholarPubMed
Worobey, M. & Holmes, E. C. (1999). Evolutionary aspects of recombination in RNA viruses. Journal of General Virology, 80, 2535–2543.CrossRefGoogle ScholarPubMed
Worobey, M., Rambaut, A., Pybus, O. G., & Robertson, D. L. (2002). Questioning the evidence for genetic recombination in the 1918 “Spanish flu” virus. Science, 296, 211a.CrossRefGoogle ScholarPubMed
Wright, S. (1931). Evolution in Mendelian populations. Genetics, 16, 97–159.Google ScholarPubMed
Xia, X. & Xie, Z. (2001). DAMBE: data analysis in molecular biology and evolution. Journal of Heredity, 92, 371–373.CrossRefGoogle ScholarPubMed
Xia, X. (1998). The rate heterogeneity of nonsynonymous substitutions in mammalian mitochondrial genes. Molecular Biology and Evolution, 15, 336–344.CrossRefGoogle ScholarPubMed
Xia, X., Hafner, M. S., & Sudman, P. D. (1996). On transition bias in mitochondrial genes of pocket gophers. Journal of Molecular Evolution, 43, 32–40.CrossRefGoogle ScholarPubMed
Xia, X. H., Xie, Z., & Kjer, K. M. (2003). 18S ribosomal RNA and tetrapod phylogeny. Systematic Biology, 52, 283–295.CrossRefGoogle ScholarPubMed
Xia, X. H., Xie, Z., Salemi, M., Chen, L., & Wang, Y. (2003). An index of substitution saturation and its application. Molecular Phylogenetics and Evolution, 26, 1–7.CrossRefGoogle ScholarPubMed
Xia, X. & Xie, Z. (2001). DAMBE: Software package for data analysis in molecular biology and evolution. Journal of Heredity, 92, 371–373.CrossRefGoogle ScholarPubMed
Yamada, S., Gotoh, O., & Yamana, H. (2006). Improvement in accuracy of multiple sequence alignment using novel group-to-group sequence alignment algorithm with piecewise linear gap cost. BMC Bioinformatics, 7, 524.CrossRefGoogle ScholarPubMed
Yamaguchi, Y. & Gojobori, T. (1997). Evolutionary mechanisms and population dynamics of the third variable envelope region of HIV within single hosts. Proceedings of the National Academy of Sciences, USA, 94(4), 1264–1269.CrossRefGoogle ScholarPubMed
Yang, Z. (1994a). Estimating the pattern of nucleotide substitution. Journal of Molecular Evolution, 39, 105–111.CrossRefGoogle ScholarPubMed
Yang, Z. (1994b). Maximum-likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods. Journal of Molecular Evolution, 39, 306–314.CrossRefGoogle ScholarPubMed
Yang, Z. (1995). A space-time process model for the evolution of DNA sequences. Genetics, 139(2), 993–1005.Google ScholarPubMed
Yang, Z. (1996). Maximum-likelihood models for combined analyses of multiple sequence data. Journal of Molecular Evolution, 42, 587–596.CrossRefGoogle ScholarPubMed
Yang, Z. (1997). PAML: a program package for phylogenetic analysis by maximum likelihood. Computing in Applied Biosciences, 13(5), 555–556.Google ScholarPubMed
Yang, Z. (1998). Likelihood ratio tests for detecting positive selection and application to primate lysozyme evolution. Molecular Biology and Evolution, 15, 568–573.CrossRefGoogle ScholarPubMed
Yang, Z. (2000). Phylogenetic Analysis by Maximum Likelihood (PAML), version 3.0. University College, London, UK.Google Scholar
Yang, Z. & Bielawski, J. P. (2000). Statistical methods for detecting molecular adaptation. Trends in Ecology and Evolution, 15(12), 496–503.CrossRefGoogle ScholarPubMed
Yang, Z. & Nielsen, R. (1998). Synonymous and nonsynonymous rate variation in nuclear genes of mammals. Journal of Molecular Evolution, 46, 409–418.CrossRefGoogle ScholarPubMed
Yang, Z. & Nielsen, R. (2002). Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Molecular Biology and Evolution, 19(6), 908–917.CrossRefGoogle ScholarPubMed
Yang, Z., Goldman, N., & Friday, A. E. (1995). Maximum likelihood trees from DNA sequences: a peculiar statistical estimation problem. Systematic Biology, 44, 384–399.CrossRefGoogle Scholar
Yang, Z., Wong, W. S. W., & Nielsen, R. (2005). Bayes empirical Bayes inference of amino acid sites under positive selection. Molecular Biology and Evolution, 22(4), 1107–1118.CrossRefGoogle ScholarPubMed
Yang, Z. H. (2000). Maximum likelihood estimation on large phylogenies and analysis of adaptive evolution in human influenza virus A. Journal of Molecular Evolution, 51, 423–432.CrossRefGoogle ScholarPubMed
Yang, Z. H. (2006). Computational Molecular Evolution. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
Yang, Z. H., Nielsen, R., Goldman, N., & Pedersen, A. M. K. (2000). Codon-substitution models for heterogeneous selection pressure at amino acid sites. Genetics, 155, 431–449.Google ScholarPubMed
Yoder, A. D. & Yang, Z. (2000). Estimation of primate speciation dates using local molecular clocks. Molecular Biology of Evolution, 17(7), 1081–1090.CrossRefGoogle ScholarPubMed
Zhang, J. (2005). On the evolution of codon volatility. Genetics, 169(1), 495–501.CrossRefGoogle ScholarPubMed
Zhang, J., Nielsen, R., & Yang, Z. (2005). Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level. Molecular Biology and Evolution, 22(12), 2472–2479.CrossRefGoogle ScholarPubMed
Zharkikh, A. (1994). Estimation of evolutionary distances between nucleotide sequences. Journal of Molecular Evolution, 39(3), 315–329.CrossRefGoogle ScholarPubMed
Zharkikh, A. & Li, W.-H. (1992a). Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences. I. Four taxa with a molecular clock. Molecular Biology and Evolution, 9, 1119–1147.Google ScholarPubMed
Zharkikh, A. & Li, W.-H. (1992b). Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences. II. Four taxa without a molecular clock. Journal of Molecular Evolution, 35, 356–366.CrossRefGoogle ScholarPubMed
Zharkikh, A. & Li, W.-H. (1995). Estimation of confidence in phylogeny: The complete-and-partial bootstrap technique. Molecular Phylogenetic Evolution, 4, 44–63.CrossRefGoogle ScholarPubMed
Zhou, H. & Zhou, Y. (2005). SPEM: improving multiple sequence alignment with sequence profiles and predicted secondary structures. Bioinformatics, 21(18), 3615–3621.CrossRefGoogle ScholarPubMed
Zlateva, K. T., Lemey, P., Vandamme, A. M., & Ranst, M. (2004). Molecular evolution and circulation patterns of human respiratory syncytial virus subgroup A: positively selected sites in the attachment g glycoprotein. Journal of Virology, 78, 4675–4683.CrossRefGoogle ScholarPubMed
Zuckerkandl, E. & Pauling, L. (1962). Molecular disease, evolution, and genetic heterogeneity. In Horizons in Biochemistry, ed. Kasha, M. & Pullman, B., pp. 189–225. New York: Academic Press.Google Scholar
Zuckerkandl, E. & Pauling, L. (1965). Evolutionary divergence and convergence in proteins. In Evolving Genes and Proteins, ed. Bryson, V. & Vogel, H. J., pp. 97–166. New York: Academic Press: Academic Press.CrossRefGoogle Scholar
Zwickl, D. J. (2006). Genetic algorithm approaches for the phylogenetic analysis of large biological sequence datasets under the maximum likelihood criterion. Ph.D. thesis, University of Texas, Austin, USA.

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • References
  • Edited by Philippe Lemey, University of Oxford, Marco Salemi, University of California, Irvine, Anne-Mieke Vandamme, Katholieke Universiteit Leuven, Belgium
  • Book: The Phylogenetic Handbook
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511819049.025
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • References
  • Edited by Philippe Lemey, University of Oxford, Marco Salemi, University of California, Irvine, Anne-Mieke Vandamme, Katholieke Universiteit Leuven, Belgium
  • Book: The Phylogenetic Handbook
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511819049.025
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • References
  • Edited by Philippe Lemey, University of Oxford, Marco Salemi, University of California, Irvine, Anne-Mieke Vandamme, Katholieke Universiteit Leuven, Belgium
  • Book: The Phylogenetic Handbook
  • Online publication: 05 June 2012
  • Chapter DOI: https://doi.org/10.1017/CBO9780511819049.025
Available formats
×