Fr. 70.00

Species Tree Inference - A Guide to Methods and Applications

English · Paperback / Softback

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Description

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"Inferring evolutionary relationships among a collection of organisms -- that is, their relationship to each other on the tree of life -- remains a central focus of much of evolutionary biology as these relationships provide the background for key hypotheses. For example, support for different hypotheses about early animal evolution are contingent upon the phylogenetic relationships among the earliest animal lineages. Within the last 20 years, the field of phylogenetics has grown rapidly, both in the quantity of data available for inference and in the number of methods available for phylogenetic estimation. The authors' first book, "Estimating Species Trees: Practical and Theoretical Aspects", published in 2010, gave an overview of the state of phylogenetic practice for analyzing data at the time, but much has changed since then. The goal of this book is to serve as an updated reference on current methods within the field. The book is organized in three sections, the first of which provides an overview of the analytical and methodological developments of species tree inference. Section two focuses on empirical inference. Section three explores various applications of species trees in evolutionary biology. The combination of theoretical and empirical approaches is meant to provide readers with a level of knowledge of both the advances and limitations of species-tree inference that can help researchers in applying the methods, while also inspiring future advances among those researchers with an interest in methodological development"--

About the author










Laura S. Kubatko is Professor of Statistics and of Evolution, Ecology, and Organismal Biology at The Ohio State University. L. Lacey Knowles is the Robert B. Payne Collegiate Professor of Ecology and Evolutionary Biology and Curator of Insects at the University of Michigan. They are the coeditors of Estimating Species Trees: Practical and Theoretical Aspects.

Summary

An up-to-date reference book on phylogenetic methods and applications for evolutionary biologists

The increasingly widespread availability of genomic data is transforming how biologists estimate evolutionary relationships among organisms and broadening the range of questions that researchers can test in a phylogenetic framework. Species Tree Inference brings together many of today’s leading scholars in the field to provide an incisive guide to the latest practices for analyzing multilocus sequence data.

This wide-ranging and authoritative book gives detailed explanations of emerging new approaches and assesses their strengths and challenges, offering an invaluable context for gauging which procedure to apply given the types of genomic data and processes that contribute to differences in the patterns of inheritance across loci. It demonstrates how to apply these approaches using empirical studies that span a range of taxa, timeframes of diversification, and processes that cause the evolutionary history of genes across genomes to differ.

By fully embracing this genomic heterogeneity, Species Tree Inference illustrates how to address questions beyond the goal of estimating phylogenetic relationships of organisms, enabling students and researchers to pursue their own research in statistically sophisticated ways while charting new directions of scientific discovery.

Additional text

"A very good and thorough overview of methods and applications to infer evolutionary relationship between recently diverged taxa."

Product details

Authors Laura Knowles Kubatko
Assisted by L. Lacey Knowles (Editor), Knowles L. Lacey (Editor), Laura Kubatko (Editor)
Publisher Princeton University Press
 
Languages English
Product format Paperback / Softback
Released 14.03.2023
 
EAN 9780691207605
ISBN 978-0-691-20760-5
No. of pages 352
Subjects Natural sciences, medicine, IT, technology > Biology > Ecology

Evolution, SCIENCE / Life Sciences / Ecology, SCIENCE / Life Sciences / Evolution, SCIENCE / Life Sciences / Biology, Applied ecology, Biology, life sciences

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