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Phylogenetic Analysis of Morphological Data : Two Volume Set - Pablo A. Goloboff

Phylogenetic Analysis of Morphological Data

Two Volume Set

By: Pablo A. Goloboff

Multi-Item Pack | 22 July 2022 | Edition Number 1

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Multi-Item Pack


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This two-volume book is an up-to-date revision of methods and principles of phylogenetic analysis of morphological data. It is also a general guide for using the computer program TNT in the analysis of such data. The book covers the main aspects of phylogenetic analysis, and general methods to compare classifications derived from molecules and morphology. Practical application of all principles discussed is illustrated by reference to TNT, a freely available software package that can perform all the steps needed in a phylogenetic analysis.

Key Features

  • Provides in depth discussion of the connections between hypotheses of homology and the parsimony criterion
  • Helps understand the basis for designing different aspects of a morphological study, from hints on delimiting the problem and data collecting, to character definitions and analysis
  • Discusses the applicability of statistical models coopted from sequence analysis to the analysis of morphological data
  • Gives detailed descriptions of the principles behind algorithms for evaluating and searching phylogenetic trees
  • Presents extensive information on commands and options of the TNT computer program
Industry Reviews

"There is no question that Goloboff provides a rigorous, logical and analytically sound framework for analyzing data - probably the most carefully considered rationale that has ever been published for phylogenetics of any kind of data ... "

- Andrew Brower, Assistant Director at USDA Animal and Plant Health Inspection Service (APHIS)

"... this book is focused on phylogenetic analyses based on morphological date [and] paleontologists will find its content particularly useful. ... provide[s] both researchers and students alike with the theoretical bases and tools for the correct building of robust phylogenetic data matrices, their analysis, and subsequent interpretation. [this book] will become a 'must-read' ..."

- M. D.Ezcurra in Ameghiniana, 2024, vol 61 (1).

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