Mathematics

A Mathematical Primer of Molecular Phylogenetics Xuhua Xia, PhD Ordering Info/Buy Book

Published. Available now. Pub Date: April 2020 Hardback Price: See Ordering info Hard ISBN: 9781771887557 Paperback ISBN:  9781774630068 E-Book ISBN: 9780429425875 Pages: 380pp + index Binding Type: hardback / paperback / ebook Notes: 8 color and 77 b/w illustrations

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Reviews
“A highly effective volume ideal as textbook for an advanced undergraduate course or for seasoned biologists seeking deeper understanding of applying mathematical approaches to address fundamental questions in phylogeny and evolution. . . . In his latest book, Xia (Univ. of Ottawa) offers a treatment of phylogenetics deeply rooted in mathematical principles yet conversational in tone. Though the book is certainly best suited to an audience with background in mathematics and statistics, readers whose primary focus is molecular or evolutionary biology will find that chapter preambles offer an effective bridge between biological concepts and their mathematical treatment in phylogenetics. Xia’s frequent references to papers that use phylogenetic methods to resolve essential evolutionary questions also work to make the methods presented accessible to a broad readership. Though minimalist in presentation, Xia’s illustrations of concepts—including sequence alignment—successfully capture the essence of complex inference techniques. Moreover, rather than simply presenting mathematical expressions, Xia provides specific numeric examples, offering readers the opportunity to check their understanding by working through problems themselves. . . . Summing Up: Highly recommended. Upper-division undergraduates. Graduate students and faculty.”
—CHOICE (publication of the Association of College and Research Libraries), review by D. P. Genereux, Broad Institute of Harvard University and Massachusetts Institute of Technology

“A nice job of presenting detailed worked analyses and of making strong connections to empirical settings, making it a useful reference for those wishing for a deeper description of these aspects. . . . Professor Xia has gone to considerable effort to provide examples that are based on empirical data, as well as worked details for the analyses performed on these data. These aspects of the book differ from many of the standard books on this topic, where toy examples and more abstract descriptions of the methodology are often provided instead.”
—Systematic Biology, review by Laura Kubatko, Ohio State University, USA

“Gives the lay of the land in computing on DNA sequence data to reconstruct evolutionary history. The volume sensibly progresses from aligning raw sequences with one another to the models that describe their mutations and onwards to the construction of phylogenetic trees from these data, with the nuts and bolts of each method described and exemplified along the way. Professor Xia doesn’t shy away from challenging us; for example, where he treats the application of affine functions in alignment algorithms, he warns us that this is something ‘only a very good student can understand.‘ Yet his explanations are so concrete and laced with pseudocode and references to real-world implementations that they invite the reader to experiment and figure out what’s going on. The Primer is geared towards researchers who are familiar with the tools and methods of the field but who now, finally, want to know how they actually work and be able to implement them by themselves. For this audience, Xia’s work compares favorably where there is overlap in subject matter with Felsenstein’s Inferring Phylogenies. For example, where the Farris algorithm is described in prose by Felsenstein, Xia helpfully describes possible implementations (using bitmasks, as connoisseurs will understand). Along the way, the reader is treated to illustrative anecdotes and the occasional, charming Canadianism: the code samples in the book are provided in MAPLE, which, we are told, is ‘a beautiful Canadian product.‘ The same could be said about the Primer, and I wish it had been around when I was a graduate student.”
—Dr. Rutger Vos, Naturalis Biodiversity Center, The Netherlands

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Now Available in Paperback

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This volume, A Mathematical Primer of Molecular Phylogenetics, offers a unique perspective on a number of phylogenetic issues that have not been covered in detail in previous publications. The volume provides sufficient mathematical background for young mathematicians and computational scientists, as well as mathematically inclined biology students, to make a smooth entry into the expanding field of molecular phylogenetics. The book will also provide sufficient details for researchers in phylogenetics to understand the workings of existing software packages used.

The volume offers comprehensive but detailed numerical illustrations to render difficult mathematical and computational concepts in molecular phylogenetics accessible to a variety of readers with different academic background.

The text includes examples of solved problems after each chapter, which will be particularly helpful for fourth-year undergraduates, postgraduates, and postdoctoral students in biology, mathematics and computer sciences. Researchers in molecular biology and evolution will find it very informative as well.

Key features:

• Provides mathematical background for young mathematicians and computational scientists to understand the expanding field of molecular phylogenetics
• Includes information for researchers in phylogenetics to understand the workings of existing software packages used in phylogenetics
• Offers a unique perspective on a number of phylogenetic issues that have not been covered in detail in previous publications
• Provides support via a comprehensive software package (DAMBE), written by the book’s author
• Aims to act as a middle ground for effective interdisciplinary communication among molecular biologists, mathematics, and computational scientists

CONTENTS:
Preface

1. Introduction to Molecular Phylogenetics
Genetic Markers are Trustworthy
Success Stories in the Application of DNA and RNA a as Genetic Markers
Two Key Objectives of Molecular Phylogenetics

2. Sequence Alignment Algorithms
Poor Alignment Introduces Not Only Noise but Also Phylogenetic Bias
Pairwise Alignment
Multiple Sequence Alignment (MSA)
Sequence Alignment with Secondary Structure
Align Nucleotide Sequences against Amino Acid Sequences

3. Nucleotide Substitution Models and Evolutionary Distances
Introduction
Three Methods to Obtain Transition Probabilities
How Far Can We Trace Back the Evolutionary History?
Selecting the Best-Fitting Substitution Model
Empirical Substitution Matrix
Visualizing Substitution Saturation
Beyond Time Reversible Models

4. Protein and Codon Substitution Models and Their Evolutionary Distances
Evolutionary Distance from Amino Acid Substitution Model
Problems with the Empirical Amino Acid Substitution Matrix
Codon-Based Models and Associated Distances

5. Substitution Rate Heterogeneity Over Sites
Causes for Rate Heterogeneity Over Sites
Gamma Distribution and Gamma Distances
Estimating the Shape Parameter of a Gamma Distribution
Contrasting Rate Heterogeneity Over Sites among Three Codon Positions
Comparison of Distances with or Without Correction

6. Maximum Parsimony Method in Phylogenetics
Introduction
The Fitch Algorithm
The Sankoff Algorithm
Contrasting MP and Ml
The Uphill Search and Branch-And-Bound Search Algorithms
The Long-Branch Attraction Problem
Statistical Tests of Alternative Topologies
Bootstrapping and Delete-Half Jackknifing

7. Distance-Based Phylogenetic Methods
Introduction
Evolutionary Distances
Distance-Based Phylogenetic Algorithms
Dating Speciation and Gene Duplication Events
Imputing Evolutionary Distances
Different Criteria are Generally Consistent with Each Other

8. Maximum Likelihood Methods in Phylogenetics
Introduction
Likelihood Method in Phylogenetic Reconstruction
A Strange Phylogenetic Bias in the Likelihood Method
Likelihood Method and Molecular Clock
Handling of Missing Data with the Pruning Algorithm (and Potential Bias)
Phylogenetic Incongruence Test

9. Phylogeny-Based Comparative Methods
Introduction
The Necessity of Phylogeny-Based Comparative Method
The Comparative Method for Continuous Characters

10. Appendix
The Delta Method for Deriving Parameter Variance
Illustration of Expectation-Maximization (EM) Algorithm
Multiple Comparisons and the Method of False Discovery Rate

Index

About the Authors / Editors:
Xuhua Xia, PhD
Professor, Biology Department, University of Ottawa, Ontario, Canada

Xuhua Xia, PhD, has been a professor of biology at the University of Ottawa, Canada, since 2009. Prior to that, he was an assistant professor at the University of Hong Kong in 1996, and served in 2001 as a senior scientist and head of Bioinformatics Laboratory in the then-newly established HKU-Pasteur Research Centre. Dr. Xia currently serves as associate editor for the Journal of Heredity. He has published 10 papers in the journal Molecular Biology and Evolution either as the first author or corresponding author and has published several papers in the journals Systematic Biology and Molecular Phylogenetics and Evolution. He has also published three books on bioinformatics, molecular evolution, and comparative genomics. According to Google Scholar, on May 4, 2018, his 2001 paper in Journal of Heredity was cited 2152 times, his 2003 paper in Molecular Phylogenetics and Evolution 877 times, and his 2013 paper in Molecular Biology and Evolution 554 times. Dr. Xia is the author of the widely used software package DAMBE, which is freely available at http://dambe.bio.uottawa.ca. Dr. Xia’s current research is on developing bioinformatic algorithms and software to meet the challenge of analyzing high-throughput data acquisition methods, optimization of translation machinery to facilitate the production of proteins and vaccines in biopharmaceutical industry, and interaction and evolution of macromolecules over time and space to understand the origin and maintenance of biodiversity. Dr. Xia earned his PhD in population biology from University of Western Ontario.

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