Phylogenetic trees in bioinformatics

Current Bioinformatics

Volumn 5, Issue 1, 2010, Pages 40-52

  Burr, Tom ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

Bootstrap; Inference methods; Markov chain monte carlo; Nucleotide substitution models; Phylogenetic trees; Population history

Indexed keywords

HUMAN IMMUNODEFICIENCY VIRUS PROTEIN; MITOCHONDRIAL DNA;

BIOINFORMATICS; COMPUTER PROGRAM; DISEASE TRANSMISSION; DNA SEQUENCE; GENE TRANSFER; HUMAN; MATHEMATICAL GENETICS; MOLECULAR EVOLUTION; MONTE CARLO METHOD; PHYLOGENY; PRIORITY JOURNAL; QUALITY CONTROL; REVIEW;

ANIMALIA; OTUS;

EID: 77950173211     PISSN: 15748936     EISSN: None     Source Type: Journal    
DOI: 10.2174/157489310790596367     Document Type: Review

References (74)

1. Grenfell B, Pybus O, Gog J, et al. Holmes E. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 2004; 303: 327-32.
2. Grassley N, Harvey P, Holmes E. Population dynamics of HIV-1 inferred from gene sequences, Genetics 1999; 151: 427-38.
3. Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 1981; 3: 368-76.
4. Kingman J. On the genealogy of large populations. J Appl Prob 1982; 19: 27-43.
5. Burr T, Myers G, Hyman J. The origin of AIDS darwinian or Lamarkian? Philos Trans R Soc Lond 2001; 356: 877-87.
6. Cann R, Stoneking M, Wilson A. Mitochondrial DNA and human evolution, Nature 1987; 325: 31-36.
7. Ingman M, Kaessmann H, Paabo S, Gyllensten U. Mitochondrial genome variation and the origin of modern humans, Nature 2000; 408: 708-13.
8. Li S, Pearl D, Doss H. Phylogenetic tree construction using Markov Chain Monte Carlo, J Am Stat Assoc 2000; 95: 493-508.
9. Revel L, Harmon L, Collar D. Phylogenetic signal, evolutionary process, and rate, Syst Biol 2008; 57(4): 591-601.
10. Lemey P, Pybus O, Rambaut A, et al. The molecular population genetics of HIV-1 group O, Genetics 2004; 167: 1059-68.
11. Pybus O, Rambaut A, Holmes E, Harvey P. New inferences from tree shape: numbers of missing taxa and population growth rates, Syst Biol 2002; 51(6): 881-88.
12. Strimer K, Pybus O. Exploring the demographic history of DNA sequences using the generalized skyline plot, Mol Biol Evol 2001; 18: 2298-2305.
13. Tavare S, Balding D, Griffiths F, Donnely P. Inferring doalescent times from DNA sequence data, Genetics 1997; 145: 505-18.
14. Sjodin P, Kaj K, Krone S, Lascoux M, Nordborg M. On the meaning and existence of an effective population size, Genetics 2005; 169: 1061-70.
15. Drummond A, Goode M. Virtual Computer and Evolutionary Biology Laboratory (vCEBL) http: //www.cebl.auckland.ac.nz/pages/-vcebl.html
16. nd ed. 1996; pp. 407-514 Hillis et al., eds. Sunderland, Massachusetts: Sinauer Associates.
17. Waddell P, Steel M. General time-reversible distances with unequal rates across sites: mixing G and inverse Gaussian distributions with invariant sites, Mol Phylogenet Evol 1997; 8(3): 398-14.
18. Press W, Robins H. Isochores exhibit evidence of genes interacting with the large-scale genomic environment, Genetics 2006; 174: 1029-40.
19. Yang Y, Chen Y, Li W. The Influence of adjacent nucleotides on the pattern of nucleotide substitution in mitochondrial introns of angiosperms, J Mol Evol 2002; 55: 111-15.
20. Leitner T, Escanilla D, Franzen C, Uhlen M, Albert J. Accurate reconstruction of a known HIV-1 transmission history by phylogenetic tree analysis, Proc Natl Acad Sci USA 1996; 93: 10864-69.
21. Huelsenbeck J, Rannala B. Phylogenetic methods come of age: testing hypotheses in an evolutionary context, Science 1997; 276: 227-32.
22. Leitner T, Kumar, S, Albert J. Tempo and mode of nucleotide substitutions in gag and env gene fragments in HIV type 1 populations with a known transmission history, Virology 1997; 71: 4761-70.
23. Gilks W, Richardson S, Spiegelhalter D. Markov Chain Monte Carlo in practice, New York, Chapman and Hall/CRC: 1996.
24. Aldous D. Stochastic models and descriptive statistics for phylogenetic trees, from Yule to today, Stat Sci 2001; 16(1): 23-34.
25. Bruno W, Socci N, Halpern A. Weighted neighbor joining: a likelihood-based approach to distance-based phylogeny reconstruction, Mol Biol Evol 2000; 17: 189-97.
26. Felsenstein J. Confidence limits on phylogenies: an approach using the bootstrap, Evolution 1985; 39: 783-91.
27. Lewis P. A genetic algorithm for maximum likelihood phylogeny inference using nucleotide sequence data, Mol Biol Evol 1998; 15: 277-82.
28. Zharkikh A, Li, W. Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences. I. Four taxa with a molecular clock, Mol Biol Evol 1992; 9: 1119-47.
29. Hillis D, Bull J. An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis, Syst Biol 1993; 42: 182-92.
30. Efron B, Halloran E, Holmes S. Bootstrap confidence levels for phylogenetic trees Proc Natl Acad Sci USA 1996; 93: 13429-34.
31. Felsenstein J, Kishino H. Is there something wrong with the bootstrap on phylogenies? A reply to Hillis and Bull, Syst Biol 1993; 42: 193-200.
32. Newton M. Bootstrapping phylogenies: large deviations and disperson effects, Biometrika 1996; 83 (2): 315-28.
33. Critchlow D, Pearl D, Qian C. The triples distance for rooted bifurcating phylogenetic trees, Syst Biol 1996; 45: 323-34.
34. Burr T, Doak J, Gattiker J, Stanbro W. Assessing confidence in phylogenetic trees: bootstrap versus Markov Chain Monte Carlo. Proceedings of the International Confereence on Mathematical and Engineering Techniques in Medicine and Biological Scienes. Las Vegas, NV, USA 2002; 1: 181-7.
35. Mar J, Harlow T, Ragan M. Bayesian and maximum likelihood phylogenetic analyses of protein sequence data under relative branch-length differences and model violation, BMC Evol Biol 2005; 5: 8, doi: 10.1186/1471-2148-5-8.
36. Burr T, Gattiker J, Gerrish P. An investigation of error sources and their impact in estimating the time to the most recent ancestor of spatially and temporally distributed HIV sequences, Stat Med 2003; 22: 1495-1516.
37. Korber B, Muldoon M, Theiler J, et al. Timing the ancestor of the HIV-1 pandemic strains, Science 2000; 288: 1789-96.
38. Rambaut A. Estimating the rate of molecular evolution: incorporating non-conttemporaneous sequences into maximum likelihood phylogenies, Bioinformatics 2000; 16: 395-9.
39. Bruno W, Halpern A. Topological bias and inconsistency of maximum likelihood using wrong models, Mol Biol Evol 1999; 16: 564-6.
40. Posada D, Crandall K. Modeltest: testing the model of DNA substitution. Bioinformatics 1998; 14: 817-18.
41. Mau B, Newton M, Larget B. Bayesian phylogenetic inference via Markov Chain Monte Carlo method. Biometrics 1999; 55: 1-12.
42. http: //evolution.genetics.washington.edu/phylip.html
43. http: //tree.bio.ed.ac.uk/software/seqgen/
44. Burr T, Skourikhine A, Bruno W, Macken C. Confidence Measures for Evolutionary Trees: Applications to Molecular Epidemiology, Proceedings of the IEEE International Conference on Information, Intelligence and Systems, Genetics and Evolution Section, Washington DC, USA 1999; pp. 107-14.
45. Stamatakis et al. RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees, Bioinformatics 2004; 21: 456-63.
46. Bergsten J. A review of long-branch attraction, Cladistics 2005; 21: 163-93.
47. Drummond A, Rambaut A. Beast: Bayesian evolutionary analysis by sampling trees, BMC Evol Biol 2007; 7: 214-27.
48. MrBayes, Bayesian inference of phylogeny (http: //mrbayes. csit.fsu.edu/index.php) Bioinformatics 2001; 17: 754-55.
49. Hillis D, Bull J, White M, Badgett M, Molineus I. Experimental phylogenetics: generation of a known phylogeny, Science 1992; 225: 589-92.
50. Naylor G, Brown W. Structural biology and phylogenetic estimation, Nature 1997; 388: 528.
51. Ou CY, Ciesielski CA, Myers G, et al. Molecular epidemiology of HIV transmission in a dental practice, Science 1992; 256: 1165-71.
52. Templeton R. The 'Eve' hypothesis: a genetic critique and reanalysis, Am Anthropol 1993; 95: 51-72.
53. Wang Q, Salter L, Pearl D. Estimation of evolutionary parameters with phylogenetic trees, J Mol Evol 2002; 55: 684-95.
54. Doss H. Some thoughts on future directions in Bayesian model selection, Stat Sin 2007; 17: 413-21
55. Posada D, Buckley T. Model selection and model averaging in phylogenetics: advantages of the AIC and Bayesian approaches over likelihood ratio tests, Syst Biol 2004; 53: 793-808.
56. Hahn B, Shaw G, De Cock K, Sharp P. AIDS as a zoonosis: scientific and public health implication, Science 2000; 287: 607-14.
57. Korber B, Myers G. Signature pattern analysis: a method for assessing viral sequence relatedness, AIDS Res Hum Retroviruses 1992;. 8, 1549-60.
58. Sharp P, Bailes E, Chaudhuri R, Rodenburg C, Santiago M, Hahn B. The origins of acquired immune deficienty syndrome viruses: where and when? Philosph Trans R Soc Lond 2001; 356: 867-76.
59. Burr T, Gattiker, J, LaBerge G. Genetic subtyping using cluster analysis. SIGKDD Explor 2002; 3: 33-42.
60. Hraber P, Kuiken C, Waugh M, Geer S, Bruno W, Leitner T. Classification of hepatitis C virus and human immunodeficiency virus-1 sequence with the branching index, J Gen Virol 2008; 89: 2098-107.
61. Tagle D, Koop B, Goodman M, Slightom J, Hess D, Jones R. Embryonic epsilon and gamma globin genes of a prosimian primate (Galago crassicaudatus). Nucleotide and amino acid sequences, developmental regulation and phylogenetic footprints, J Mol Biol 1988; 203: 439-55.
62. Brocchieri L. Phylogenetic inferences from molecular sequences: review and critique, Theor Popul Biol 2001; 59: 27-40.
63. Mossel E, Vigoda E. Limitations of Markov chain monte carlo algorithms for Bayesian inference of phylogeny, Ann Appl Prob 2006; 16: 2215-34.
64. Evans S, Warnow T. Unidentifiable divergence times in ratesacross-sites models, IEEE Trans Comp Biol Bioinformatics 2004; 1(1): 130-4.
65. Jenkins G, Rambaut A, Pybus O, Holmes E. Rates of molecular evolution in RNA viruses: a quantitative phylogenetic analysis, J Mol Evol 2002; 54: 156-65.
66. Peng B, Kimmel M. SimuPOP: a Forward-time population genetics simulation environment, Bioinformatics 2005; 21: 3686-87.
67. st Century: An overview and prospects of coalescent theory. Theor Popul Biol 1999; 56: 1-10.
68. Felsenstein J, Kuhner M, Yamato J, Beerli P. Likelihoods on coalescents: a Monte Carlo sampling approach to inferring parameters from population samples of molecular data in Statistics in Molecular Biology and Genetics, ed. Francoise Seillier-Moiseiwitsch. IMS Lecture Notes-Monograph Series, Inst Math Stat Am Math Soc Hayward: California 1999; vol. 33: pp. 163-85.
69. Pybus O, Rambaut A. GENIE: estimation demographic history from molecular phylogenies. Bioinformatics 2002; 18: 1404-05.
70. Schierup M, Hein J. Consequences of recombination on traditional phylogenetic analysis, Genetics 2000; 156: 879-91.
71. Snir S, Tuller T. The net-hmm approach: phylogenetic network inference by combining maximum likelihood and hidden Markov models, J Bioinformatics Comp Biol 2009; 7: 625-44.
72. Cardona G, Llabres M, Rossello F, Valiente G. Metrics for Phylogenetic networks II: nodal and triplets matrics, IEEE Trans Comp Biol Bioinformatics 2009; 6: 454-69.
73. Satija R, Pachter L, Hein J. Combining statistical alignment and phylogenetic footprinting to detect regulatory elements, Bioinformatics 2008; 24: 1236-42.
74. DeFonzo V, Aluffi-Pentini F, Parisi, V. Hidden Markov models in bioinformatics, Curr Bioinformatics 2007; 2: 49-61.