Inferring Phylogenies Ebook

Phylogenies, or evolutionary trees, are the basic structures necessary to think about and analyze differences between species. Statistical, computational, and algorithmic work in this field has been ongoing for four decades now, and there have been great advances in understanding. Yet no book has summarized this work. Inferring Phylogenies does just that in a single, compact volume. Phylogenies are inferred with various kinds of data. This book concentrates on some of the central ones: discretely coded characters, molecular sequences, gene frequencies, and quantitative traits. Also covered are restriction sites, RAPDs, and microsatellites.

This is the first book on "phylogenetic supertrees", a recent, but controversial development for inferring evolutionary trees. Rather than analyze the combined primary character data directly, supertree construction proceeds by combining the tree topologies derived from those data. This difference in strategy has allowed for the exciting possibility of larger, more complete phylogenies than are otherwise currently possible, with the potential to revolutionize evolutionarily-based research. This book provides a comprehensive look at supertrees, ranging from the methods used to build supertrees to the significance of supertrees to bioinformatic and biological research. Reviews of many the major supertree methods are provided and four new techniques, including a Bayesian implementation of supertrees, are described for the first time. The far-reaching impact of supertrees on biological research is highlighted both in general terms and through specific examples from diverse clades such as flowering plants, even-toed ungulates, and primates. The book also critically examines the many outstanding challenges and problem areas for this relatively new field, showing the way for supertree construction in the age of genomics. Interdisciplinary contributions from the majority of the leading authorities on supertree construction in all areas of the bioinformatic community (biology, computer sciences, and mathematics) will ensure that this book is a valuable reference with wide appeal to anyone interested in phylogenetic inference.

Committed to Excellence in the Landmark Tenth Edition. This edition continues the evolution of Raven & Johnson’s Biology. The author team is committed to continually improving the text, keeping the student and learning foremost. We have integrated new pedagogical features to expand the students’ learning process and enhance their experience in the ebook. This latest edition of the text maintains the clear, accessible, and engaging writing style of past editions with the solid framework of pedagogy that highlights an emphasis on evolution and scientific inquiry that have made this a leading textbook for students majoring in biology and have been enhanced in this landmark Tenth edition. This emphasis on the organizing power of evolution is combined with an integration of the importance of cellular, molecular biology and genomics to offer our readers a text that is student friendly and current. Our author team is committed to producing the best possible text for both student and faculty. The lead author, Kenneth Mason, University of Iowa, has taught majors biology at three different major public universities for more than fifteen years. Jonathan Losos, Harvard University, is at the cutting edge of evolutionary biology research, and Susan Singer, Carleton College, has been involved in science education policy issues on a national level. All three authors bring varied instructional and content expertise to the tenth edition of Biology.

This book integrates a wide variety of data analysis methods into a single and flexible interface: the R language. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters.

Phylogenies in Ecology is the first book to critically review the application of phylogenetic methods in ecology, and it serves as a primer to working ecologists and students of ecology wishing to understand these methods. This book demonstrates how phylogenetic information is transforming ecology by offering fresh ways to estimate the similarities and differences among species, and by providing deeper, evolutionary-based insights on species distributions, coexistence, and niche partitioning. Marc Cadotte and Jonathan Davies examine this emerging area's explosive growth, allowing for this new body of hypotheses testing. Cadotte and Davies systematically look at all the main areas of current ecophylogenetic methodology, testing, and inference. Each chapter of their book covers a unique topic, emphasizes key assumptions, and introduces the appropriate statistical methods and null models required for testing phylogenetically informed hypotheses. The applications presented throughout are supported and connected by examples relying on real-world data that have been analyzed using the open-source programming language, R. Showing how phylogenetic methods are shedding light on fundamental ecological questions related to species coexistence, conservation, and global change, Phylogenies in Ecology will interest anyone who thinks that evolution might be important in their data.

Biology Ebook

'Phylogenetics' is the reconstruction and analysis of phylogenetic (evolutionary) trees and networks based on inherited characteristics. It is a flourishing area of intereaction between mathematics, statistics, computer science and biology.The main role of phylogenetic techniques lies in evolutionary biology, where it is used to infer historical relationships between species. However, the methods are also relevant to a diverse range of fields including epidemiology, ecology, medicine, as well as linguistics and cognitive psychologyThis graduate-level book, based on the authors lectures at The University of Canterbury, New Zealand, focuses on the mathematical aspects of phylogenetics. It brings together the central results of the field (providing proofs of the main theorem), outlines their biological significance,and indicateshow algorithms may be derived. The presentation is self-contained and relies on discrete mathematics with some probability theory. A set of exercises and at least one specialist topic ends each chapter.This book is intended for biologists interested in the mathematical theory behind phylogenetic methods, and for mathematicians, statisticians, and computer scientists eager to learn about this emerging area of discrete mathematics.'Phylogenetics' in the 24th volume in the Oxford Lecture Series in Mathematics and its Applications. This series contains short books suitable for graduate students and researchers who want a well-written account of mathematics that is fundamental to current to research. The series emphasises futuredirections of research and focuses on genuine applications of mathematics to finance, engineering and the physical and biological sciences.

This volume presents a compelling collection of state-of-the-art work in algorithmic computational biology, honoring the legacy of Professor Bernard M.E. Moret in this field. Reflecting the wide-ranging influences of Prof. Moret’s research, the coverage encompasses such areas as phylogenetic tree and network estimation, genome rearrangements, cancer phylogeny, species trees, divide-and-conquer strategies, and integer linear programming. Each self-contained chapter provides an introduction to a cutting-edge problem of particular computational and mathematical interest. Topics and features: addresses the challenges in developing accurate and efficient software for the NP-hard maximum likelihood phylogeny estimation problem; describes the inference of species trees, covering strategies to scale phylogeny estimation methods to large datasets, and the construction of taxonomic supertrees; discusses the inference of ultrametric distances from additive distance matrices, and the inference of ancestral genomes under genome rearrangement events; reviews different techniques for inferring evolutionary histories in cancer, from the use of chromosomal rearrangements to tumor phylogenetics approaches; examines problems in phylogenetic networks, including questions relating to discrete mathematics, and issues of statistical estimation; highlights how evolution can provide a framework within which to understand comparative and functional genomics; provides an introduction to Integer Linear Programming and its use in computational biology, including its use for solving the Traveling Salesman Problem. Offering an invaluable source of insights for computer scientists, applied mathematicians, and statisticians, this illuminating volume will also prove useful for graduate courses on computational biology and bioinformatics.

Seminal papers by A. W. F. Edwards, published together for the first time with commentaries from leading experts to contextualise his contribution.