An up-to-date reference book on phylogenetic methods and applications for evolutionary biologistsThe 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 pr...

Now updated with the latest research, this pioneering, accessible study argues for a more complex view of evolution—proposing there is more to heredity than just genes.In this revised edition the widely read Evolution in Four Dimensions, Eva Jablonka and Marion Lamb propose that there are four “dimensions” in heredity. These four inheritance systems play a role in evolution which, they argue, can all provide variations upon which natural selection can act:...

Noam Chomsky and Robert Berwick draw on recent developments in linguistic theory to offer an evolutionary account of language and our remarkable, species-specific ability to acquire it.“A loosely connected collection of four essays that will fascinate anyone interested in the extraordinary phenomenon of language.”—New York Review of BooksWe are born crying, but those cries signal the first stirring of language. Within a year...

Statistical Bioinformatics provides a balanced treatment of statistical theory in the context of bioinformatics applications. Designed for a one or two semester senior undergraduate or graduate bioinformatics course, the text takes a broad view of the subject – not just gene expression and sequence analysis, but a careful balance of statistical theory in the context of bioinformatics applications. The inclusion of R & SAS code as well as the development of advanced methodology such as Baye...

This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamental...

The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to...

The Phylogenetic Handbook is a broad, hands on guide to theory and practice of nucleotide and protein phylogenetic analysis. This second edition includes six new chapters, covering topics such as Bayesian inference, tree topology testing and the impact of recombination on phylogenies, as well as a detailed section on molecular adaptation. The book has a stronger focus on hypothesis testing than the previous edition, with more extensive discussions on recombination analysis, detecting molec...

What are the models used in phylogenetic analysis and what exactly is involved in Bayesian evolutionary analysis using Markov chain Monte Carlo (MCMC) methods? How can you choose and apply these models, which parameterisations and priors make sense, and how can you diagnose Bayesian MCMC when things go wrong? These are just a few of the questions answered in this comprehensive overview of Bayesian approaches to phylogenetics. This practical guide: • Addresses the theoretical aspects of the...

Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods. The flood of genomic data has generated an acute need for powerful statistical methods and efficient computational algorithms to enable their effective analysis and interpretation. Molecular Evolution: a statistical approach presents and ex...

LANDSCAPE GENETICS: CONCEPTS, METHODS, APPLICATIONSLANDSCAPE GENETICS: CONCEPTS, METHODS, APPLICATIONSEdited by Niko Balkenhol, Samuel A. Cushman, Andrew T. Storfer, Lisette P. WaitsLandscape genetics is an exciting and rapidly growing field, melding methods and theory from landscape ecology and population genetics to address some of the most challenging and urgent ecological and evolutionary topics of our time. Lan...

This unique book addresses the statistical modelling and analysis of microbiome data using cutting-edge R software. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of R for data analysis step by step. The data and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, so that these new methods can be readily applied in their own research....

Providing genome-informed personalized treatment is a goal of modern medicine. Identifying new translational targets in nucleic acid characterizations is an important step toward that goal. The information tsunami produced by such genome-scale investigations is stimulating parallel developments in statistical methodology and inference, analytical frameworks, and computational tools. Within the context of genomic medicine and with a strong focus on cancer research, this book describes the i...