From Genetics to Mathematics

From Genetics to Mathematics
Author: Miroslaw Lachowicz
Publisher: World Scientific
Total Pages: 242
Release: 2009
Genre: Science
ISBN: 9812837256

This volume contains pedagogical and elementary introductions to genetics for mathematicians and physicists as well as to mathematical models and techniques of population dynamics. It also offers a physicist''s perspective on modeling biological processes. Each chapter starts with an overview followed by the recent results obtained by authors. Lectures are self-contained and are devoted to various phenomena such as the evolution of the genetic code and genomes, age-structured populations, demography, sympatric speciation, the Penna model, Lotka-Volterra and other predator-prey models, evolutionary models of ecosystems, extinctions of species, and the origin and development of language. Authors analyze their models from the computational and mathematical points of view.

Foundations of Mathematical Genetics

Foundations of Mathematical Genetics
Author: Anthony William Fairbank Edwards
Publisher: Cambridge University Press
Total Pages: 138
Release: 2000-01-13
Genre: Science
ISBN: 9780521775441

A definitive account of the origins of modern mathematical population genetics, first published in 2000.

Some Mathematical Models from Population Genetics

Some Mathematical Models from Population Genetics
Author: Alison Etheridge
Publisher: Springer Science & Business Media
Total Pages: 129
Release: 2011-01-07
Genre: Mathematics
ISBN: 3642166318

This work reflects sixteen hours of lectures delivered by the author at the 2009 St Flour summer school in probability. It provides a rapid introduction to a range of mathematical models that have their origins in theoretical population genetics. The models fall into two classes: forwards in time models for the evolution of frequencies of different genetic types in a population; and backwards in time (coalescent) models that trace out the genealogical relationships between individuals in a sample from the population. Some, like the classical Wright-Fisher model, date right back to the origins of the subject. Others, like the multiple merger coalescents or the spatial Lambda-Fleming-Viot process are much more recent. All share a rich mathematical structure. Biological terms are explained, the models are carefully motivated and tools for their study are presented systematically.

Mathematical and Statistical Methods for Genetic Analysis

Mathematical and Statistical Methods for Genetic Analysis
Author: Kenneth Lange
Publisher: Springer Science & Business Media
Total Pages: 376
Release: 2012-12-06
Genre: Medical
ISBN: 0387217509

Written to equip students in the mathematical siences to understand and model the epidemiological and experimental data encountered in genetics research. This second edition expands the original edition by over 100 pages and includes new material. Sprinkled throughout the chapters are many new problems.

Mathematical Population Genetics 1

Mathematical Population Genetics 1
Author: Warren J. Ewens
Publisher: Springer Science & Business Media
Total Pages: 448
Release: 2004-01-09
Genre: Science
ISBN: 9780387201917

This is the first of a planned two-volume work discussing the mathematical aspects of population genetics with an emphasis on evolutionary theory. This volume draws heavily from the author’s 1979 classic, but it has been revised and expanded to include recent topics which follow naturally from the treatment in the earlier edition, such as the theory of molecular population genetics.

Mathematical Structures in Population Genetics

Mathematical Structures in Population Genetics
Author: Yuri I. Lyubich
Publisher: Springer
Total Pages: 0
Release: 2011-12-14
Genre: Mathematics
ISBN: 9783642762130

Mathematical methods have been applied successfully to population genet ics for a long time. Even the quite elementary ideas used initially proved amazingly effective. For example, the famous Hardy-Weinberg Law (1908) is basic to many calculations in population genetics. The mathematics in the classical works of Fisher, Haldane and Wright was also not very complicated but was of great help for the theoretical understanding of evolutionary pro cesses. More recently, the methods of mathematical genetics have become more sophisticated. In use are probability theory, stochastic processes, non linear differential and difference equations and nonassociative algebras. First contacts with topology have been established. Now in addition to the tra ditional movement of mathematics for genetics, inspiration is flowing in the opposite direction, yielding mathematics from genetics. The present mono grapll reflects to some degree both patterns but especially the latter one. A pioneer of this synthesis was S. N. Bernstein. He raised-and partially solved- -the problem of characterizing all stationary evolutionary operators, and this work was continued by the author in a series of papers (1971-1979). This problem has not been completely solved, but it appears that only cer tain operators devoid of any biological significance remain to be addressed. The results of these studies appear in chapters 4 and 5. The necessary alge braic preliminaries are described in chapter 3 after some elementary models in chapter 2.

Information Geometry and Population Genetics

Information Geometry and Population Genetics
Author: Julian Hofrichter
Publisher: Springer
Total Pages: 323
Release: 2017-02-23
Genre: Mathematics
ISBN: 3319520458

The present monograph develops a versatile and profound mathematical perspective of the Wright--Fisher model of population genetics. This well-known and intensively studied model carries a rich and beautiful mathematical structure, which is uncovered here in a systematic manner. In addition to approaches by means of analysis, combinatorics and PDE, a geometric perspective is brought in through Amari's and Chentsov's information geometry. This concept allows us to calculate many quantities of interest systematically; likewise, the employed global perspective elucidates the stratification of the model in an unprecedented manner. Furthermore, the links to statistical mechanics and large deviation theory are explored and developed into powerful tools. Altogether, the manuscript provides a solid and broad working basis for graduate students and researchers interested in this field.

100 Most Important Science Ideas

100 Most Important Science Ideas
Author: Mark Henderson
Publisher:
Total Pages: 0
Release: 2011
Genre: Mathematics
ISBN: 9781554079483

100 Most Important Science Ideas presents a selection of 100 key concepts in science in a series of concise and accessible essays that are understandable to the layperson. The authors explain the answers to the most exciting and important scientific questions, which have had a profound influence on our way of life. Helpful diagrams, everyday examples and enlightening quotations highlight the straightforward text. All the big ideas that readers would expect to find are present, and each is discussed over two to four pages. The authors use concrete applications to describe many of the abstract ideas, and some entries have a timeline along the bottom showing when the idea originated and its development. Examples are: What can DNA reveal about the history of human evolution? Why does the moon orbit the Earth while the Earth orbits the sun? How will genetic medicine revolutionize healthcare? How did chaos theory become so ordered? 100 Most Important Science Ideas also includes brief biographies of iconic scientists and entertaining anecdotes from the world of scientific discovery. It is an indispensable overview of science for anyone who wants to understand the world around them.

Probability and Mathematical Genetics

Probability and Mathematical Genetics
Author: N. H. Bingham
Publisher: Cambridge University Press
Total Pages: 546
Release: 2010-07-15
Genre: Mathematics
ISBN: 9780521145770

Focusing on the work of Sir John Kingman, one of the world's leading researchers in probability and mathematical genetics, this book touches on the important areas of these subjects in the last 50 years. Leading authorities give a unique insight into a wide range of currently topical problems. Papers in probability concentrate on combinatorial and structural aspects, in particular exchangeability and regeneration. The Kingman coalescent links probability with mathematical genetics and is fundamental to the study of the latter. This has implications across the whole of genomic modeling including the Human Genome Project. Other papers in mathematical population genetics range from statistical aspects including heterogeneous clustering, to the assessment of molecular variability in cancer genomes. Further papers in statistics are concerned with empirical deconvolution, perfect simulation, and wavelets. This book will be warmly received by established experts as well as their students and others interested in the content.

Mathematical and Statistical Methods for Genetic Analysis

Mathematical and Statistical Methods for Genetic Analysis
Author: Kenneth Lange
Publisher: Springer Science & Business Media
Total Pages: 277
Release: 2013-04-17
Genre: Mathematics
ISBN: 1475727399

Geneticists now stand on the threshold of sequencing the genome in its entirety. The unprecedented insights into human disease and evolution offered by mapping and sequencing are transforming medicine and agriculture. This revolution depends vitally on the contributions made by applied mathematicians, statisticians, and computer scientists. Kenneth Lange has written a book to enable graduate students in the mathematical sciences to understand and model the epidemiological and experimental data encountered in genetics research. Mathematical, statistical, and computational principles relevant to this task are developed hand-in-hand with applications to gene mapping, risk prediction, and the testing of epidemiological hypotheses. The book covers many topics previously only accessible in journal articles, such as pedigree analysis algorithms, Markov chain, Monte Carlo methods, reconstruction of evolutionary trees, radiation hybrid mapping, and models of recombination. The whole is backed by numerous exercise sets.