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Twenty-four articles from the November 1996 workshop investigate the reconstruction of trees or ranking hierarchies from dissimilarity or entity-to-character data, the use of hierarchies for modeling evolution and other processes, and the combining of gene trees. Included are mathematical treatments of hierarchies in the frameworks of set systems, linear subspaces, graph objects, and tree metrics in their analyses. Such current applications as learning robots, intron evolution, and the development of language are addressed. Annotation copyrighted by Book News, Inc., Portland, OR.
Over the past few decades numerous scientists have called for a unification of the fields of embryo development, genetics, and evolution. Each field has glaring holes in its ability to explain the fundamental phenomena of life. In this book, the author shows how the phenomenon of cell differentiation, considered in its temporal and spatial aspects during embryogenesis, provides a starting point for a unified theory of multicellular organisms (plants, fungi and animals), including their evolution and genetics. This unification is based on the recent discovery of differentiation waves by the author and his colleagues, described in the appendices, and illustrated by a flip movie prepared by a medical artist. To help the reader through the many fields covered, a glossary is included.This book will be of great value to the researcher and practicing doctors/scientists alike. The research students will receive an in-depth tutorial on the topics covered. The seasoned researcher will appreciate the applications and the gold mine of other possibilities for novel research topics.
The natural world is infinitely complex and hierarchically structured, with smaller units forming the components of progressively larger systems: molecules make up cells, cells comprise tissues and organs that are, in turn, parts of individual organisms, which are united into populations and integrated into yet more encompassing ecosystems. In the face of such awe-inspiring complexity, there is a need for a comprehensive, non-reductionist evolutionary theory. Having emerged at the crossroads of paleobiology, genetics, and developmental biology, the hierarchical approach to evolution provides a unifying perspective on the natural world and offers an operational framework for scientists seeking to understand the way complex biological systems work and evolve. Coedited by one of the founders of hierarchy theory and featuring a diverse and renowned group of contributors, this volume provides an integrated, comprehensive, cutting-edge introduction to the hierarchy theory of evolution. From sweeping historical reviews to philosophical pieces, theoretical essays, and strictly empirical chapters, it reveals hierarchy theory as a vibrant field of scientific enterprise that holds promise for unification across the life sciences and offers new venues of empirical and theoretical research. Stretching from molecules to the biosphere, hierarchy theory aims to provide an all-encompassing understanding of evolution and—with this first collection devoted entirely to the concept—will help make transparent the fundamental patterns that propel living systems.
This book considers evolution at different scales: sequences, genes, gene families, organelles, genomes and species. The focus is on the mathematical and computational tools and concepts, which form an essential basis of evolutionary studies, indicate their limitations, and give them orientation. Recent years have witnessed rapid progress in the mathematics of evolution and phylogeny, with models and methods becoming more realistic, powerful, and complex. Aimed at graduates and researchers in phylogenetics, mathematicians, computer scientists and biologists, and including chapters by leading scientists: A. Bergeron, D. Bertrand, D. Bryant, R. Desper, O. Elemento, N. El-Mabrouk, N. Galtier, O. Gascuel, M. Hendy, S. Holmes, K. Huber, A. Meade, J. Mixtacki, B. Moret, E. Mossel, V. Moulton, M. Pagel, M.-A. Poursat, D. Sankoff, M. Steel, J. Stoye, J. Tang, L.-S. Wang, T. Warnow, Z. Yang, this book of contributed chapters explains the basis and covers the recent results in this highly topical area.
The first book to systematically introduce the emerging area of phylogenetic combinatorics.
This book is devoted to a novel conceptual theoretical framework of neuro science and is an attempt to show that we can postulate a very small number of assumptions and utilize their heuristics to explain a very large spectrum of brain phenomena. The major assumption made in this book is that inborn and acquired neural automatisms are generated according to the same func tional principles. Accordingly, the principles that have been revealed experi mentally to govern inborn motor automatisms, such as locomotion and scratching, are used to elucidate the nature of acquired or learned automat isms. This approach allowed me to apply the language of control theory to describe functions of biological neural networks. You, the reader, can judge the logic of the conclusions regarding brain phenomena that the book derives from these assumptions. If you find the argument flawless, one can call it common sense and consider that to be the best praise for a chain of logical conclusions. For the sake of clarity, I have attempted to make this monograph as readable as possible. Special attention has been given to describing some of the concepts of optimal control theory in such a way that it will be under standable to a biologist or physician. I have also included plenty of illustra tive examples and references designed to demonstrate the appropriateness and applicability of these conceptual theoretical notions for the neurosciences.
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.
This book investigates the mathematical analysis of biological invasions. Unlike purely qualitative treatments of ecology, it draws on mathematical theory and methods, equipping the reader with sharp tools and rigorous methodology. Subjects include invasion dynamics, species interactions, population spread, long-distance dispersal, stochastic effects, risk analysis, and optimal responses to invaders. While based on the theory of dynamical systems, including partial differential equations and integrodifference equations, the book also draws on information theory, machine learning, Monte Carlo methods, optimal control, statistics, and stochastic processes. Applications to real biological invasions are included throughout. Ultimately, the book imparts a powerful principle: that by bringing ecology and mathematics together, researchers can uncover new understanding of, and effective response strategies to, biological invasions. It is suitable for graduate students and established researchers in mathematical ecology.
'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.
Provides a unique comprehensive review of axiomatic consensus theory in biomathematics as it has developed over the past 30 years.