An Introduction to Genetic Statistics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download An Introduction to Genetic Statistics PDF full book. Access full book title An Introduction to Genetic Statistics by Oscar Kempthorne. Download full books in PDF and EPUB format.
Author: Oscar Kempthorne Publisher: Wiley-Blackwell ISBN: Category : Science Languages : en Pages : 576
Book Description
Elementary probability; Random mating populations; Elementary selection problems; The elementary stochastic theory of genetic populations; Inbreeding; The generation matrix theory of inbreeding; Tests of genetic hypotheses; The estimation of genetic parameters; The planning of experiments; Statistical problems in human genetics; The analysis of variation; The partition of variance; Multiple regression, correlation and adjustment of data, and path analysis; Inheritance of quantitative characters in a random mating population; Non-random mating deploid populations with one locus segregating; Correlation between relatives under inbreeding with one locus segregating; One-locus polyploid populations; Diploid populations with arbitrary number of segregating loci and arbitrary epistacy; Inbreeding with a arbitrary diploid population; Population derived from inbred lines; Infinitesimal equilibrium theory of assortative mating; Selection for quantitative characters.
Author: Melinda C. Mills Publisher: MIT Press ISBN: 0262538385 Category : Science Languages : en Pages : 433
Book Description
A comprehensive introduction to modern applied statistical genetic data analysis, accessible to those without a background in molecular biology or genetics. Human genetic research is now relevant beyond biology, epidemiology, and the medical sciences, with applications in such fields as psychology, psychiatry, statistics, demography, sociology, and economics. With advances in computing power, the availability of data, and new techniques, it is now possible to integrate large-scale molecular genetic information into research across a broad range of topics. This book offers the first comprehensive introduction to modern applied statistical genetic data analysis that covers theory, data preparation, and analysis of molecular genetic data, with hands-on computer exercises. It is accessible to students and researchers in any empirically oriented medical, biological, or social science discipline; a background in molecular biology or genetics is not required. The book first provides foundations for statistical genetic data analysis, including a survey of fundamental concepts, primers on statistics and human evolution, and an introduction to polygenic scores. It then covers the practicalities of working with genetic data, discussing such topics as analytical challenges and data management. Finally, the book presents applications and advanced topics, including polygenic score and gene-environment interaction applications, Mendelian Randomization and instrumental variables, and ethical issues. The software and data used in the book are freely available and can be found on the book's website.
Author: Palmer, Lyle J. Publisher: Policy Press ISBN: 1861348975 Category : Medical Languages : en Pages : 240
Book Description
This book brings together leading experts to provide an introduction to genetic epidemiology that begins with a primer in human molecular genetics through all the standard methods in population genetics and genetic epidemiology required for an adequate grounding in the field.
Author: David J. Balding Publisher: John Wiley & Sons ISBN: 9780470997628 Category : Science Languages : en Pages : 1616
Book Description
The Handbook for Statistical Genetics is widely regarded as the reference work in the field. However, the field has developed considerably over the past three years. In particular the modeling of genetic networks has advanced considerably via the evolution of microarray analysis. As a consequence the 3rd edition of the handbook contains a much expanded section on Network Modeling, including 5 new chapters covering metabolic networks, graphical modeling and inference and simulation of pedigrees and genealogies. Other chapters new to the 3rd edition include Human Population Genetics, Genome-wide Association Studies, Family-based Association Studies, Pharmacogenetics, Epigenetics, Ethic and Insurance. As with the second Edition, the Handbook includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between the chapters, tying the different areas together. With heavy use of up-to-date examples, real-life case studies and references to web-based resources, this continues to be must-have reference in a vital area of research. Edited by the leading international authorities in the field. David Balding - Department of Epidemiology & Public Health, Imperial College An advisor for our Probability & Statistics series, Professor Balding is also a previous Wiley author, having written Weight-of-Evidence for Forensic DNA Profiles, as well as having edited the two previous editions of HSG. With over 20 years teaching experience, he’s also had dozens of articles published in numerous international journals. Martin Bishop – Head of the Bioinformatics Division at the HGMP Resource Centre As well as the first two editions of HSG, Dr Bishop has edited a number of introductory books on the application of informatics to molecular biology and genetics. He is the Associate Editor of the journal Bioinformatics and Managing Editor of Briefings in Bioinformatics. Chris Cannings – Division of Genomic Medicine, University of Sheffield With over 40 years teaching in the area, Professor Cannings has published over 100 papers and is on the editorial board of many related journals. Co-editor of the two previous editions of HSG, he also authored a book on this topic.
Author: Melanie Mitchell Publisher: MIT Press ISBN: 9780262631853 Category : Computers Languages : en Pages : 226
Book Description
Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.
Author: Kenneth Lange Publisher: Springer Science & Business Media ISBN: 0387217509 Category : Medical Languages : en Pages : 376
Book Description
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.
Author: Andrea S. Foulkes Publisher: Springer Science & Business Media ISBN: 038789554X Category : Science Languages : en Pages : 264
Book Description
Statistical genetics has become a core course in many graduate programs in public health and medicine. This book presents fundamental concepts and principles in this emerging field at a level that is accessible to students and researchers with a first course in biostatistics. Extensive examples are provided using publicly available data and the open source, statistical computing environment, R.
Author: Anthony J.F. Griffiths Publisher: Macmillan ISBN: 9780716768876 Category : Science Languages : en Pages : 872
Book Description
Provides an introduction to genetic analysis. This book covers contemporary genetics, and helps students understand the essentials of genetics, featuring various experiments, teaching them how to analyze data, and how to draw their own conclusions
Author: M.C. Yang Publisher: CRC Press ISBN: 9789056991340 Category : Mathematics Languages : en Pages : 264
Book Description
Although the basic statistical theory behind modern genetics is not very difficult, most statistical genetics papers are not easy to read for beginners in the field, and formulae quickly become very tedious to fit a particular area of application. Introduction to Statistical Methods in Modern Genetics distinguishes between the necessary and unnecessary complexity in a presentation designed for graduate-level statistics students. The author keeps derivations simple, but does so without losing the mathematical details. He also provides the required background in modern genetics for those looking forward to entering this arena. Along with some of the statistical tools important in genetics applications, students will learn: How a gene is found How scientists have separated the genetic and environmental aspects of a person's intelligence How genetics are used in agriculture to improve crops and domestic animals What a DNA fingerprint is and why there are controversies about it Although the author assumes students have a foundation in basic statistics, an appendix provides the necessary background beyond the elementary, including multinomial distributions, inference on frequency tables, and discriminant analysis. With clear explanations, a multitude of figures, and exercise sets in each chapter, this text forms an outstanding entrée into the rapidly expanding world of genetic data analysis.
Author: Oscar Kempthorne
Author: Oscar Kempthorne
Author: Melinda C. Mills
Author: Palmer, Lyle J.
Author: David J. Balding
Author: Melanie Mitchell
Author: Alan E. H. Emery
Author: Kenneth Lange
Author: Andrea S. Foulkes
Author: Anthony J.F. Griffiths
Author: M.C. Yang