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side get 0, the leaves on the other side get 1, and the missing leaves get ?), and the matrices are concatenated and then analyzed using heuristics for maximum parsimony. Another approach for supertree construction include a maximum likelihood version of MRP called "MRL" (matrix representation with likelihood), which analyzes the same MRP matrix but uses heuristics for maximum likelihood instead of for maximum parsimony to construct the supertree.
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Robinson-Foulds differences between the (binary) supertree and each input tree. In this case the supertree can hence be view as the median of the input tree according to the
Robinson-Foulds distance. Alternative approaches have been developed to infer median supertree based on different metrics, e.g. relying on triplet or quartet decomposition of the trees.
44:
The most well known method for supertree construction is Matrix
Representation with Parsimony (MRP), in which the input source trees are represented by matrices with 0s, 1s, and ?s (i.e., each edge in each source tree defines a bipartition of the leafset into two disjoint parts, and the leaves on one
27:
assembled from a combination of smaller phylogenetic trees, which may have been assembled using different datasets (e.g. morphological and molecular) or a different selection of taxa. Supertree algorithms can highlight areas where additional data would most usefully resolve any ambiguities. The
52:
distance is the most popular of many ways of measuring how similar a supertree is to the input trees. It is a metric for the number of clades from the input trees that are retained in the supertree. Robinson-Foulds optimization methods search for a supertree that minimizes the total (summed)
36:
The construction of a supertree scales exponentially with the number of taxa included; therefore for a tree of any reasonable size, it is not possible to examine every possible supertree and weigh its success at combining the input information.
75:
and mammals. They have also been applied to larger-scale problems such as the origins of diversity, vulnerability to extinction, and evolutionary models of ecological structure.
673:
Bininda-Emonds, O.; Cardillo, M.; Jones, K.; MacPhee, R.; Beck, R.; Grenyer, R.; Price, S.; Vos, R.; Gittleman, J.; Purvis, A. (2007). "The delayed rise of present-day mammals".
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Additional methods include the Min Cut
Supertree approach, Most Similar Supertree Analysis (MSSA), Distance Fit (DFIT) and Quartet Fit (QFIT), implemented in the software CLANN.
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41:
methods are thus essential, although these methods may be unreliable; the result extracted is often biased or affected by irrelevant characteristics of the input data.
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A recent innovation has been the construction of
Maximum Likelihood supertrees and the use of "input-tree-wise" likelihood scores to perform tests of two supertrees.
724:
Davies, T.; Fritz, S.; Grenyer, R.; Orme, C.; Bielby, J.; Bininda-Emonds, O.; Cardillo, M.; Jones, K.; Gittleman, J.; Mace, G. M.; Purvis, A. (2008).
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96:
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Gordon, A. (1986). "Consensus supertrees: the synthesis of rooted trees containing overlapping sets of labeled leaves".
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Webb, C. O.; Ackerly, D. D.; McPeek, M. A.; Donoghue, M. J. (2002). "Phylogenies and
Community Ecology".
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Akanni, Wasiu A.; Creevey, Christopher J.; Wilkinson, Mark; Pisani, Davide (2014-06-12).
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Mark A. Ragan (1992). "Phylogenetic inference based on matrix representation of trees".
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Supertrees have been applied to produce phylogenies of many groups, notably the
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Proceedings of the
National Academy of Sciences of the United States of America
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Proceedings of the
National Academy of Sciences of the United States of America
520:. Methods in Molecular Biology. Vol. 537. Humana Press. pp. 139–161.
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360:"L.U.St: a tool for approximated maximum likelihood supertree reconstruction"
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303:"S uper T riplets : a triplet-based supertree approach to phylogenomics"
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575:"Darwin's abominable mystery: Insights from a supertree of the angiosperms"
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462:"Clann: investigating phylogenetic information through supertree analyses"
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input trees of a supertree should behave as samples from the larger tree.
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Ranwez, Vincent; Criscuolo, Alexis; Douzery, Emmanuel J.P. (2010-06-15).
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Phylogenetic supertrees: combining information to reveal the tree of life
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110:(2002). "The (Super)Tree of Life: Procedures, Problems, and Prospects".
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511:"Trees from Trees: Construction of Phylogenetic Supertrees Using Clann"
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Bansal, M.; Burleigh, J.; Eulenstein, O.; Fernández-Baca, D. (2010).
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634:"Supertrees disentangle the chimerical origin of eukaryotic genomes"
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810:
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726:"Phylogenetic trees and the future of mammalian biodiversity"
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459:
509:Creevey, C. J.; McInerney, J. O. (2009-01-01).
460:Creevey, C. J.; McInerney, J. O. (2005-02-01).
632:Pisani, D.; Cotton, J.; McInerney, J. (2007).
16:Phylogenetic tree combining multiple sub-trees
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257:
153:
151:
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106:Bininda-Emonds, O. R. P.; Gittleman, J. L.;
732:. 105 Suppl 1 (Supplement_1): 11556–11563.
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793:10.1146/annurev.ecolsys.33.010802.150448
781:Annual Review of Ecology and Systematics
518:Bioinformatics for DNA Sequence Analysis
124:10.1146/annurev.ecolsys.33.010802.150511
112:Annual Review of Ecology and Systematics
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419:"A supertree method for rooted trees"
260:Molecular Phylogenetics and Evolution
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1068:Phylogenetic comparative methods
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164:Algorithms for Molecular Biology
85:Bininda-Emonds, O. R. P (2004).
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557:Davies, T.; Barraclough, T.;
479:10.1093/bioinformatics/bti020
446:10.1016/S0166-218X(00)00202-X
319:10.1093/bioinformatics/btq196
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423:Discrete Applied Mathematics
272:10.1016/1055-7903(92)90035-F
160:"Robinson-Foulds supertrees"
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993:Phylogenetic reconciliation
900:Evolutionary biology portal
856:Computational phylogenetics
526:10.1007/978-1-59745-251-9_7
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516:. In Posada, David (ed.).
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1183:Phylogenetic nomenclature
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225:Journal of Classification
210:"Supertree: Introduction"
377:10.1186/1471-2105-15-183
212:. genome.cs.iastate.edu.
1063:Molecular phylogenetics
1013:Distance-matrix methods
861:Molecular phylogenetics
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600:10.1073/pnas.0308127100
1083:Phylogenetics software
997:Probabilistic methods
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177:10.1186/1748-7188-5-18
876:Evolutionary taxonomy
651:10.1093/molbev/msm095
1035:Three-taxon analysis
941:Phylogenetic network
32:Construction methods
1078:Phylogenetic signal
738:2008PNAS..10511556D
695:10.1038/nature05634
687:2007Natur.446..507B
591:2004PNAS..101.1904D
417:Semple, C. (2000).
1006:Bayesian inference
1001:Maximum likelihood
364:BMC Bioinformatics
237:10.1007/BF01894195
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988:Maximum parsimony
981:Inference methods
929:Phylogenetic tree
681:(7135): 507–512.
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313:(12): i115–i123.
98:978-1-4020-2328-6
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69:angiosperms
63:Application
866:Cladistics
567:Soltis, D.
563:Soltis, P.
370:(1): 183.
140:References
73:eukaryotes
1203:Supertree
1167:Polyphyly
1162:Paraphyly
1157:Monophyly
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934:Cladogram
559:Chase, M.
488:1367-4803
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327:1367-4811
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245:122146129
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573:(2004).
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