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Volumn 17, Issue 3, 2000, Pages 401-405

On the optimization principle in phylogenetic analysis and the minimum- evolution criterion

Author keywords

Agglomerative approach; Criterion to be optimized; Model of the data; Optimal and heuristic algorithms; Phylogenetic reconstruction

Indexed keywords

ALGORITHM; ARTICLE; DNA HYBRIDIZATION; NONHUMAN; NUCLEOTIDE SEQUENCE; PHYLOGENY; TAXONOMY;

EID: 0034003343     PISSN: 07374038     EISSN: None     Source Type: Journal    
DOI: 10.1093/oxfordjournals.molbev.a026319     Document Type: Article
Times cited : (29)

References (28)
  • 1
    • 0000540861 scopus 로고    scopus 로고
    • The performance of the NJ method of phylogeny reconstruction
    • B. MIRKIN, F. R. MCMORRIS, F. S. ROBERTS, and A. RZHETSKY, eds. American Mathematical Society, Providence, R.I.
    • ATTESON, K. 1997. The performance of the NJ method of phylogeny reconstruction. Pp. 133-148 in B. MIRKIN, F. R. MCMORRIS, F. S. ROBERTS, and A. RZHETSKY, eds. Mathematical hierarchies and biology. American Mathematical Society, Providence, R.I.
    • (1997) Mathematical Hierarchies and Biology , pp. 133-148
    • Atteson, K.1
  • 2
    • 0026005922 scopus 로고
    • Use of the method of generalized least squares in reconstructing phylogenies from sequence data
    • BULMER, M. 1991. Use of the method of generalized least squares in reconstructing phylogenies from sequence data. Mol. Biol. Evol. 8:868-883.
    • (1991) Mol. Biol. Evol. , vol.8 , pp. 868-883
    • Bulmer, M.1
  • 3
    • 0002022265 scopus 로고
    • Hierarchical cluster methods as maximum likelihood estimators
    • J. FELSENSTEIN, ed. Springer, Berlin
    • DEGENS, P. O. 1983. Hierarchical cluster methods as maximum likelihood estimators. Pp. 249-253 in J. FELSENSTEIN, ed. Numerical taxonomy. Springer, Berlin.
    • (1983) Numerical Taxonomy , pp. 249-253
    • Degens, P.O.1
  • 5
    • 0021581577 scopus 로고
    • Distance methods for inferring phylogenies: A justification
    • FELSENSTEIN, J. 1984. Distance methods for inferring phylogenies: a justification. Evolution 38:16-24.
    • (1984) Evolution , vol.38 , pp. 16-24
    • Felsenstein, J.1
  • 6
    • 0000461280 scopus 로고
    • Confidence limits on phylogenies: An approach using the bootstrap
    • _. 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39:783-791.
    • (1985) Evolution , vol.39 , pp. 783-791
  • 7
    • 0023461388 scopus 로고
    • Estimation of hominoid phylogeny from a DNA hybridization data set
    • _. 1987. Estimation of hominoid phylogeny from a DNA hybridization data set. J. Mol. Evol. 26:123-131.
    • (1987) J. Mol. Evol. , vol.26 , pp. 123-131
  • 8
    • 0003437299 scopus 로고
    • Distributed by the author, Department of Genetics, University of Washington, Seattle
    • _. 1993. PHYLIP (phylogeny inference package). Distributed by the author, Department of Genetics, University of Washington, Seattle.
    • (1993) PHYLIP (Phylogeny Inference Package)
  • 9
    • 0031084471 scopus 로고    scopus 로고
    • An alternating least-squares approach to inferring phylogenies from pairwise distances
    • _. 1997. An alternating least-squares approach to inferring phylogenies from pairwise distances. Syst. Biol. 46: 101-111.
    • (1997) Syst. Biol. , vol.46 , pp. 101-111
  • 10
    • 0028035267 scopus 로고
    • A note on Sattath and Tversky's, Saittou and Nei's and Studier and Keppler's algorithms for inferring phylogenies from evolutionary distances
    • GASCUEL, O. 1994. A note on Sattath and Tversky's, Saittou and Nei's and Studier and Keppler's algorithms for inferring phylogenies from evolutionary distances. Mol. Biol. Evol. 11:961-963.
    • (1994) Mol. Biol. Evol. , vol.11 , pp. 961-963
    • Gascuel, O.1
  • 12
    • 0030807655 scopus 로고    scopus 로고
    • BIONJ: An improved version of the NJ algorithm based on a simple model of sequence data
    • _. 1997a. BIONJ: an improved version of the NJ algorithm based on a simple model of sequence data. Mol. Biol. Evol. 14:685-695.
    • (1997) Mol. Biol. Evol. , vol.14 , pp. 685-695
  • 13
    • 0000194822 scopus 로고    scopus 로고
    • Concerning the NJ algorithm and its unweighted version, UNJ
    • B. MIRKIN, F. R. MCMORRIS, F. S. ROBERTS, and A. RZHETSKY, eds. American Mathematical Society, Providence, R.I.
    • _. 1997b. Concerning the NJ algorithm and its unweighted version, UNJ. Pp. 149-170 in B. MIRKIN, F. R. MCMORRIS, F. S. ROBERTS, and A. RZHETSKY, eds. Mathematical hierarchies and biology. American Mathematical Society, Providence, R.I.
    • (1997) Mathematical Hierarchies and Biology , pp. 149-170
  • 14
    • 0034360426 scopus 로고    scopus 로고
    • Data model and classification by trees: The minimum variance reduction (MVR) method
    • in press
    • _. 2000. Data model and classification by trees: the minimum variance reduction (MVR) method, J. Classif. (in press).
    • (2000) J. Classif.
  • 15
    • 0025061094 scopus 로고
    • Limitations of the evolutionary parsimony method of phylogenetic analysis
    • JIN, L., and M. NEI. 1990. Limitations of the evolutionary parsimony method of phylogenetic analysis. Mol. Biol. Evol. 7:82-102.
    • (1990) Mol. Biol. Evol. , vol.7 , pp. 82-102
    • Jin, L.1    Nei, M.2
  • 16
    • 0019296687 scopus 로고
    • A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences
    • KIMURA, M. 1980. A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16:111-120.
    • (1980) J. Mol. Evol. , vol.16 , pp. 111-120
    • Kimura, M.1
  • 17
    • 0029917260 scopus 로고    scopus 로고
    • A stepwise algorithm for finding minimum evolution trees
    • KUMAR, S. 1996. A stepwise algorithm for finding minimum evolution trees. Mol. Biol. Evol. 13:584-593.
    • (1996) Mol. Biol. Evol. , vol.13 , pp. 584-593
    • Kumar, S.1
  • 18
    • 0001179368 scopus 로고
    • Similarity analysis by reciprocal pairs for discrete and continuous data
    • MCQUITTY, L. L. 1966. Similarity analysis by reciprocal pairs for discrete and continuous data. Educ. Psychol. Meas. 26: 825-831.
    • (1966) Educ. Psychol. Meas. , vol.26 , pp. 825-831
    • Mcquitty, L.L.1
  • 19
    • 0024658495 scopus 로고
    • Variances of the average numbers of nucleotide substitutions within and between populations
    • NEI, M., and L. JIN. 1989. Variances of the average numbers of nucleotide substitutions within and between populations. Mol. Biol. Evol. 6:290-300.
    • (1989) Mol. Biol. Evol. , vol.6 , pp. 290-300
    • Nei, M.1    Jin, L.2
  • 20
    • 0032514671 scopus 로고    scopus 로고
    • The optimization principle in phylogsnetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small
    • NEI, M., S. KUMAR, and K. TAKAHASHI, 1998. The optimization principle in phylogsnetic analysis tends to give incorrect topologies when the number of nucleotides or amino acids used is small. Proc. Natl. Acad. Sci. USA 95:12390-12397.
    • (1998) Proc. Natl. Acad. Sci. USA , vol.95 , pp. 12390-12397
    • Nei, M.1    Kumar, S.2    Takahashi, K.3
  • 21
    • 0019424782 scopus 로고
    • Comparison of phylogenetic trees
    • ROBINSON, D. F., and L. R. FOULDS. 1981. Comparison of phylogenetic trees. Math. Biosci. 53:131-147.
    • (1981) Math. Biosci. , vol.53 , pp. 131-147
    • Robinson, D.F.1    Foulds, L.R.2
  • 22
    • 0027185401 scopus 로고
    • Theoretical foundation of the minimum-evolution method of phylogenetic inference
    • RZHETSKY, A., and M. NEI. 1993. Theoretical foundation of the minimum-evolution method of phylogenetic inference. Mol. Biol. Evol. 10:1073-1095.
    • (1993) Mol. Biol. Evol. , vol.10 , pp. 1073-1095
    • Rzhetsky, A.1    Nei, M.2
  • 23
    • 0000329594 scopus 로고
    • Relative efficiencies of the Fitch-Margoliash, maximum-parsimony, maximum-likelihood, minimum-evolution, and neighbor-joining methods of phylogenetic reconstructions in obtaining the correct tree
    • SAITOU, N., and M. IMANISHI. 1989. Relative efficiencies of the Fitch-Margoliash, maximum-parsimony, maximum-likelihood, minimum-evolution, and neighbor-joining methods of phylogenetic reconstructions in obtaining the correct tree. Mol. Biol. Evol. 6:514-525.
    • (1989) Mol. Biol. Evol. , vol.6 , pp. 514-525
    • Saitou, N.1    Imanishi, M.2
  • 24
    • 0023375195 scopus 로고
    • The neighbor-joining method: A new method for reconstruction of phylogenetic trees
    • SAITOU, N., and M. NEI. 1987. The neighbor-joining method: a new method for reconstruction of phylogenetic trees. Mol. Biol. Evol. 4:406-425.
    • (1987) Mol. Biol. Evol. , vol.4 , pp. 406-425
    • Saitou, N.1    Nei, M.2
  • 25
    • 0000491446 scopus 로고
    • Additive similarity trees
    • SATTATH, S., and A. TVERSKY. 1977. Additive similarity trees. Psychometrika 42:319-345.
    • (1977) Psychometrika , vol.42 , pp. 319-345
    • Sattath, S.1    Tversky, A.2
  • 27
    • 0000825481 scopus 로고
    • A statistical method for evaluating systematic relationships
    • SOKAL, R. R., and C. D. MICHENER. 1958. A statistical method for evaluating systematic relationships. Univ. Kans. Sci. Bull. 38:1409-1438.
    • (1958) Univ. Kans. Sci. Bull. , vol.38 , pp. 1409-1438
    • Sokal, R.R.1    Michener, C.D.2
  • 28
    • 0024114801 scopus 로고
    • A note on the neighbor-joining method of Saitou and Nei
    • STUDIER, J. A., and K. J. KEPPLER. 1988. A note on the neighbor-joining method of Saitou and Nei. Mol. Biol. Evol. 5: 729-731.
    • (1988) Mol. Biol. Evol. , vol.5 , pp. 729-731
    • Studier, J.A.1    Keppler, K.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.