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Phylogenetic Supertrees

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Cover of 'Phylogenetic Supertrees'

Table of Contents

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    Book Overview
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    Chapter 1 New uses for old phylogenies
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    Chapter 2 The MRP Method
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    Chapter 3 An Assessment of Matrix Representation with Compatibility in Supertree Construction
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    Chapter 4 MRF Supertrees
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    Chapter 5 Everything You always wanted to Know about the Average Consensus, and More
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    Chapter 6 Tangled Tales from Multiple Markers
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    Chapter 7 Supertree Methods for Ancestral Divergence Dates and other Applications
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    Chapter 8 Supertree Algorithms for Nested Taxa
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    Chapter 9 Quartet Supertrees
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    Chapter 10 Bayesian Supertrees
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    Chapter 11 Some Desiderata for Liberal Supertrees
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    Chapter 12 Taxonomy, Supertrees, and the Tree of Life
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    Chapter 13 Garbage in, Garbage out
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    Chapter 14 Reconstructing Divergence Times for Supertrees
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    Chapter 15 Performance of Supertree Methods on Various Data Set Decompositions
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    Chapter 16 Unrooted Supertrees
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    Chapter 17 The Cladistics of Matrix Representation with Parsimony Analysis
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    Chapter 18 A Critique of Matrix Representation with Parsimony Supertrees
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    Chapter 19 Supertrees, Components and Three-Item Data
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    Chapter 20 A Molecular Supertree of the Artiodactyla
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    Chapter 21 Supertrees
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    Chapter 22 Using Supertrees to Investigate Species Richness in Grasses and Flowering Plants
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    Chapter 23 Detecting Diversification Rate Variation in Supertrees
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Title
Phylogenetic Supertrees
Published by
Springer Netherlands, January 2004
DOI 10.1007/978-1-4020-2330-9
ISBNs
978-1-4020-2329-3, 978-1-4020-2330-9
Editors

Bininda-Emonds, Olaf R. P.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 3%
Sweden 1 3%
Finland 1 3%
United Kingdom 1 3%
United States 1 3%
Unknown 24 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 41%
Researcher 5 17%
Professor > Associate Professor 3 10%
Student > Master 3 10%
Student > Doctoral Student 2 7%
Other 4 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 55%
Biochemistry, Genetics and Molecular Biology 3 10%
Computer Science 3 10%
Environmental Science 2 7%
Mathematics 2 7%
Other 3 10%