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Jeffrey L. ThorneProfessor of Genetics and StatisticsPhD, University
of Washington Visit the Thorne Bioinformatics Page
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Statistical tools for the analysis of DNA and protein sequencesImproving models for DNA evolution by incorporating phenotype: The relationship between phenotype and survival of the genotype is central to both genetics and evolution. A wide variety of computational biology techniques aim to predict aspects of phenotype from DNA sequence data. We are working to improve models of molecular evolution by incorporating these computational biology prediction systems. Because phenotype can induce dependence among changes that occur at different positions within a gene sequence, conventional procedures for making evolutionary inferences are not computationally tractable and new statistical procedures are needed. Our efforts have concentrated on protein tertiary structure and RNA secondary structure, but we are very excited by the potential to quantify the impacts on evolution of diverse other aspects of phenotype. Evolution of the rate of evolution: Evolutionary analysis of DNA and protein sequences is typically performed by either assuming that all evolutionary lineages change at the same rate or by avoiding any attempt to directly consider the fact that the rate of evolution changes over time. Factors that affect the rate of molecular evolution (e.g., mutation, population size, generation time, selection) change over time and therefore the rate of molecular evolution is extremely unlikely to be identical for different evolutionary lineages. However, it is reasonable to expect an autocorrelation of rates over time. Closely related evolutionary lineages tend to evolve at similar rates and distantly related lineages might evolve at more different rates. We are developing methods for estimating dates of evolutionary events from molecular sequence data without the restrictive and implausible assumption that rates of evolution have been constant over time. We also feel that these methods have great potential for illuminating patterns of evolutionary rate variation over time. Selected Publications:Thorne, J.L. (2007) Protein evolution constraints and model-based techniques to study them. Current Opinion in Structural Biology (in press) Choi, S. C., Hobolth, A., Robinson, D. M., Kishino, H., Thorne, J.L. (2007) Quantifying the impact of protein tertiary structure on molecular evolution. Mol. Biol. Evol. (in press) Thorne, J.L., Choi, S. C., Yu, J., Kishino, H. (2007) Population genetics without intraspecific data. Mol. Biol. Evol. (in press) Thorne J.L., Goldman N. (2007) Probabilistic models for the study of protein evolution. Balding, Bishop, and Cannings, eds. Handbook of Statistical Genetics, Third Edition. Wiley and Sons. (in press) Lin, Y.-M., Fang, S.-C., Thorne, J.L. (2007) A TABU search algorithm for maximum parsimony phylogeny inference. Eur. J. Operational Research 176:1908-1917. Yu, J., Thorne J.L. (2006) Dependence among sites in RNA evolution. Mol. Biol. Evol. 23(8): 1525-1537. Yu, J., Thorne, J.L. (2006) Testing for spatial clustering of amino acid replacements within protein tertiary structure. J. Mol. Evol. 62(6):682-692. Seo, T.-K., Kishino, H., Thorne, J.L. (2005) Incorporating gene-specific variation when inferring and evaluating optimal evolutionary tree topologies from multilocus sequence data. Proc. Natl. Acad. Sci. U.S.A. 102(12): 4436-4441. Thorne, J.L. and Kishino, H. (2005) Estimation of divergence times from molecular sequence data. In Statistical methods in molecular evolution. R. Nielsen, ed. Springer Verlag, pp.235-256. Seo, T.-K., Kishino, H., and Thorne, J.L. (2004) Estimating absolute rates of synonymous and nonsynonymous nucleotide substitution in order to characterize natural selection and date species divergences. Mol. Biol. Evol. 21: 1201-1213. Sanderson, M.J., Thorne, J.L., Wikstrom, N., and Bremer, K. (2004) Molecular evidence on plant divergence times. Am. J.Bot., 91:1656-1665. Thorne, J.L. 2004. Discussant (pages 584-585) on ``A Bayesian approach to DNA sequence segmentation'', a paper by Richard J. Boys and Daniel A. Henderson. Biometrics 60:573-588. Thorne, J.L. and Goldman, N. (2003) Probabilistic models for the study of protein evolution. (revised for second edition) In Handbook of Statistical Genetics, Second Edition. D.J. Balding, M. Bishop, and C. Cannings, eds.John Wiley and Sons, Inc. Wiegmann BM, Yeates DK, Thorne JL, Kishino H. (2003) Time Flies: A new molecular time-scale for fly evolution without a clock. Systematic Biology 52(6):745-756. Hasegawa M, Thorne JL, Kishino H (2003) Time scale of eutherian evolution estimated without assuming constant rate of molecular evolution. Genes and Genetic Systems 78(4): 267-283. (review) Robinson DM, Jones DT, Kishino H, Goldman N, Thorne JL (2003) Protein evolution with dependence among codons due to tertiary structure. Mol.Biol. Evol. 20(10):1692-1704. Scholl EH, Thorne JL, McCarter JP, Bird DM. (2003) Horizontally transferred genes in plant-parasitic nematodes: A high-throughput genomic approach. Genome Biology 4(6):R39. Kishino H, Thorne JL (2002) Bayesian hierarchical model of rate of molecular evolution. Proceedings of the Institute of Statistical Mathematics.50(1): 17-31 (in Japanese). Bird, D. McK., Clifton, S. W., Kepler, T., Kieber, J.J., Thorne, J. and C. H. Opperman (2002) Genomic dissection of a nematode-plant interaction:A tool to study plant biology. Plant Physiology 129:394-395. Seo T-K, Thorne JL, Hasegawa M, Kishino H (2002) Estimation of effective population size of HIV-1 within a host: A pseudomaximum-likelihood approach. Genetics 160: 1283-1293. Thorne JL, Kishino H (2002) Divergence time estimation and rate evolution with multilocus data sets. Systematic Biology 51:689-702. Seo T-K, Thorne JL, Hasegawa M, Kishino H (2002) A Viral Sampling Design for Testing the Molecular Clock and for Estimating Evolutionary Rates and Divergence Times. Bioinformatics 18(1):115-123. For more information contact:
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