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Statistical Population Genomics
This open access volume presents state-of-the-art inference methods in population genomics, focusing on data analysis based on rigorous statistical techniques. After introducing general concepts related to the biology of genomes and their evolution, the book covers state-of-the-art methods for the analysis of genomes in populations, including demography inference, population structure analysis and detection of selection, using both model-based inference and simulation procedures. Last but not least, it offers an overview of the current knowledge acquired by applying such methods to a large variety of eukaryotic organisms. Written in the highly successful Methods in Molecular Biology series f...
Models and Methods for Biological Evolution
Biological evolution is the phenomenon concerning how species are born, are transformed or disappear over time. Its study relies on sophisticated methods that involve both mathematical modeling of the biological processes at play and the design of efficient algorithms to fit these models to genetic and morphological data. Models and Methods for Biological Evolution outlines the main methods to study evolution and provides a broad overview illustrating the variety of formal approaches used, notably including combinatorial optimization, stochastic models and statistical inference techniques. Some of the most relevant applications of these methods are detailed, concerning, for example, the study of migratory events of ancient human populations or the progression of epidemics. This book should thus be of interest to applied mathematicians interested in central problems in biology, and to biologists eager to get a deeper understanding of widely used techniques of evolutionary data analysis.
Molecular Data Analysis Using R
This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal--the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.
Evolutionary Genomics
Together with early theoretical work in population genetics, the debate on sources of genetic makeup initiated by proponents of the neutral theory made a solid contribution to the spectacular growth in statistical methodologies for molecular evolution. Evolutionary Genomics: Statistical and Computational Methods is intended to bring together the more recent developments in the statistical methodology and the challenges that followed as a result of rapidly improving sequencing technologies. Presented by top scientists from a variety of disciplines, the collection includes a wide spectrum of articles encompassing theoretical works and hands-on tutorials, as well as many reviews with key biolog...
The Emergence of Religion in Human Evolution
Religious capacity is a highly elaborate, neurocognitive human trait that has a solid evolutionary foundation. This book uses a multidisciplinary approach to describe millions of years of biological innovations that eventually give rise to the modern trait and its varied expression in humanity’s many religions. The authors present a scientific model and a central thesis that the brain organs, networks, and capacities that allowed humans to survive physically also gave our species the ability to create theologies, find sustenance in religious practice, and use religion to support the social group. Yet, the trait of religious capacity remains non-obligatory, like reading and mathematics. The individual can choose not to use it. The approach relies on research findings in nine disciplines, including the work of countless neuroscientists, paleoneurologists, archaeologists, cognitive scientists, and psychologists. This is a cutting-edge examination of the evolutionary origins of humanity’s interaction with the supernatural. It will be of keen interest to academics working in Religious Studies, Neuroscience, Cognitive Science, Anthropology, Evolutionary Biology, and Psychology.
What, if anything, are species?
This book is an extended argument for abandoning the species rank. Instead, the author proposes that the rank of "species" be replaced by a pluralistic and multi-level view. In such a view, all clades including the smallest identifiable one would be named and studied within a phylogenetic context. What are currently called "species" represent different sorts of things depending on the sort of organisms and processes being considered. This is already the case, but is not formally recognized by those scientists using the species rank in their work. Adopting a rankless taxonomy at all levels would enhance academic studies of evolution and ecology and yield practical benefits in areas of public ...
Hidden Markov Models
This volume aims to provide a new perspective on the broader usage of Hidden Markov Models (HMMs) in biology. Hidden Markov Models: Methods and Protocols guides readers through chapters on biological systems; ranging from single biomolecule, cellular level, and to organism level and the use of HMMs in unravelling the complex mechanisms that govern these complex systems. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Hidden Markov Models: Methods and Protocols aims to demonstrate the impact of HMM in biology and inspire new research.
Ingenious
As humans evolved, we developed technologies to modify our environment, yet these innovations are increasingly affecting our behavior, biology, and society. Now we must figure out how to function in the world we’ve created. Over thousands of years, humans have invented ingenious ways to gain mastery over our environment. The ability to communicate, accumulate knowledge collectively, and build on previous innovations has enabled us to change nature. Innovation has allowed us to thrive. The trouble with innovation is that we can seldom go back and undo it. We invent, embrace, and exploit new technologies to modify our environment. Then we modify those technologies to cope with the resulting ...
Probability Models for DNA Sequence Evolution
"What underlying forces are responsible for the observed patterns of variability, given a collection of DNA sequences?" In approaching this question a number of probability models are introduced and anyalyzed.Throughout the book, the theory is developed in close connection with data from more than 60 experimental studies that illustrate the use of these results.
Modèles et méthodes pour l’évolution biologique
À l’origine de la diversité du vivant, l’évolution biologique est le phénomène par lequel les espèces naissent, se transforment ou disparaissent au cours du temps. Son étude fait intervenir des méthodes d’analyse sophistiquées qui reposent à la fois sur la modélisation mathématique des processus biologiques qui interviennent et sur la conception d’algorithmes efficaces pour ajuster ces modèles aux données génétiques et morphologiques. Modèles et méthodes pour l’évolution biologique expose les principales méthodes utilisées pour étudier l’évolution et offre un large panorama illustrant la variété des approches formelles mises en oeuvre notamment dans l’optimisation combinatoire, les modèles stochastiques, l’inférence statistique, l’échantillonnage par Monte-Carlo. Certaines des applications marquantes de ces méthodes y sont détaillées. Elles concernent, par exemple, l’étude d’événements migratoires des anciennes populations humaines ou la progression des épidémies.
