Statistical Problems In Genetics And Molecular Biology
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Statistical Problems In Genetics And Molecular Biology
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Author : Norman R. Drinkwater
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2011-12-15
Statistical Problems In Genetics And Molecular Biology written by Norman R. Drinkwater and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-15 with Medical categories.
This book evolved from the notes for a course of the same title that we've taught for the last eighteen years at the University of Wisconsin to graduate students in cancer biology, genetics, molecular biology, and other biomedical programs. We concentrate on a class of statistical methods, so-called nonparametric statistics, which requires us to make very few assumptions regarding the model that gives rise to the data. These methods are also attractive because they are usually simple to apply and have considerable intuitive appeal.
Statistics In Human Genetics And Molecular Biology
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Author : Cavan Reilly
language : en
Publisher: CRC Press
Release Date : 2009-06-19
Statistics In Human Genetics And Molecular Biology written by Cavan Reilly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-19 with Mathematics categories.
Focusing on the roles of different segments of DNA, Statistics in Human Genetics and Molecular Biology provides a basic understanding of problems arising in the analysis of genetics and genomics. It presents statistical applications in genetic mapping, DNA/protein sequence alignment, and analyses of gene expression data from microarray experiments.
Handbook Of Statistical Genetics
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Author : D. J. Balding
language : en
Publisher:
Release Date : 2001-03-28
Handbook Of Statistical Genetics written by D. J. Balding and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03-28 with Mathematics categories.
A truly groundbreaking volume, the Handbook of Statistical Genetics is a timely, informative and highly accessible reference for both statisticians interested in genetical applications and geneticists seeking a deeper understanding of statistical methods in their field. It is divided into six main sections, encompassing the entire field of statistics in genetics: ? Bioinformatics ? Population Genetics ? Evolutionary Genetics ? Genetic Epidemiology ? Plant and Animal Genetics ? Applications As the Human Genome Project (HGP) reaches its climax, with the complete sequence of mankind, science is fast approaching an exciting new stage in its ability to understand genetic forces in man. In parallel to the HGP are major sequencing efforts in other organisms, enabling us to understand broader questions in evolution and classification. This explosion of data has led to an increased need for sophisticated statistical, mathematical and computational tools to enable complex data collection, analysis and interpretation of the results. ? Comprehensive coverage of the most pressing statistical issues in genetics. ? Offers a lucid introduction to newcomers, as well as providing invaluable information for more experienced researchers. ? Each chapter is written by a leading international authority from the field. ? Complemented by numerous examples, case studies, and references to useful resources on the web. This authoritative reference will be ideal for both students and researchers working in genetics, including statisticians, geneticists, molecular biologists, biochemists and computer scientists.
Statistical Methods In Molecular Evolution
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Author : Rasmus Nielsen
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-06
Statistical Methods In Molecular Evolution written by Rasmus Nielsen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-06 with Science categories.
In the field of molecular evolution, inferences about past evolutionary events are made using molecular data from currently living species. With the availability of genomic data from multiple related species, molecular evolution has become one of the most active and fastest growing fields of study in genomics and bioinformatics. Most studies in molecular evolution rely heavily on statistical procedures based on stochastic process modelling and advanced computational methods including high-dimensional numerical optimization and Markov Chain Monte Carlo. This book provides an overview of the statistical theory and methods used in studies of molecular evolution. It includes an introductory section suitable for readers that are new to the field, a section discussing practical methods for data analysis, and more specialized sections discussing specific models and addressing statistical issues relating to estimation and model choice. The chapters are written by the leaders of field and they will take the reader from basic introductory material to the state-of-the-art statistical methods. This book is suitable for statisticians seeking to learn more about applications in molecular evolution and molecular evolutionary biologists with an interest in learning more about the theory behind the statistical methods applied in the field. The chapters of the book assume no advanced mathematical skills beyond basic calculus, although familiarity with basic probability theory will help the reader. Most relevant statistical concepts are introduced in the book in the context of their application in molecular evolution, and the book should be accessible for most biology graduate students with an interest in quantitative methods and theory. Rasmus Nielsen received his Ph.D. form the University of California at Berkeley in 1998 and after a postdoc at Harvard University, he assumed a faculty position in Statistical Genomics at Cornell University. He is currently an Ole Rømer Fellow at the University of Copenhagen and holds a Sloan Research Fellowship. His is an associate editor of the Journal of Molecular Evolution and has published more than fifty original papers in peer-reviewed journals on the topic of this book. From the reviews: "...Overall this is a very useful book in an area of increasing importance." Journal of the Royal Statistical Society "I find Statistical Methods in Molecular Evolution very interesting and useful. It delves into problems that were considered very difficult just several years ago...the book is likely to stimulate the interest of statisticians that are unaware of this exciting field of applications. It is my hope that it will also help the 'wet lab' molecular evolutionist to better understand mathematical and statistical methods." Marek Kimmel for the Journal of the American Statistical Association, September 2006 "Who should read this book? We suggest that anyone who deals with molecular data (who does not?) and anyone who asks evolutionary questions (who should not?) ought to consult the relevant chapters in this book." Dan Graur and Dror Berel for Biometrics, September 2006 "Coalescence theory facilitates the merger of population genetics theory with phylogenetic approaches, but still, there are mostly two camps: phylogeneticists and population geneticists. Only a few people are moving freely between them. Rasmus Nielsen is certainly one of these researchers, and his work so far has merged many population genetic and phylogenetic aspects of biological research under the umbrella of molecular evolution. Although Nielsen did not contribute a chapter to his book, his work permeates all its chapters. This book gives an overview of his interests and current achievements in molecular evolution. In short, this book should be on your bookshelf." Peter Beerli for Evolution, 60(2), 2006
An Introduction To Statistical Genetic Data Analysis
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Author : Melinda C. Mills
language : en
Publisher: MIT Press
Release Date : 2020-02-18
An Introduction To Statistical Genetic Data Analysis written by Melinda C. Mills and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-18 with Science categories.
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.
Computational Genome Analysis
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Author : Richard C. Deonier
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-27
Computational Genome Analysis written by Richard C. Deonier and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-27 with Computers categories.
This book presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters.
The Fundamentals Of Modern Statistical Genetics
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Author : Nan M. Laird
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-12-13
The Fundamentals Of Modern Statistical Genetics written by Nan M. Laird and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-13 with Medical categories.
This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendel’s first experiments to genome-wide association studies, the book describes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation, linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intended audience is statisticians, biostatisticians, epidemiologists and quantitatively- oriented geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or to pursue research in methodology. A background in intermediate level statistical methods is required. The authors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels. No background in genetics is assumed.
Parametric Statistical Change Point Analysis
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Author : Jie Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-11-06
Parametric Statistical Change Point Analysis written by Jie Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-11-06 with Mathematics categories.
This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More recently, change point analysis has been found in extensive applications related to analyzing biomedical imaging data and gene expression data. Extensive examples throughout the text emphasize key concepts and different methodologies used. New examples of change point analysis in modern molecular biology and other fields such as finance and air traffic control have been added to this second edition.
Handbook Of Statistical Genomics
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Author : David J. Balding
language : en
Publisher: John Wiley & Sons
Release Date : 2019-07-09
Handbook Of Statistical Genomics written by David J. Balding and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-09 with Science categories.
A timely update of a highly popular handbook on statistical genomics This new, two-volume edition of a classic text provides a thorough introduction to statistical genomics, a vital resource for advanced graduate students, early-career researchers and new entrants to the field. It introduces new and updated information on developments that have occurred since the 3rd edition. Widely regarded as the reference work in the field, it features new chapters focusing on statistical aspects of data generated by new sequencing technologies, including sequence-based functional assays. It expands on previous coverage of the many processes between genotype and phenotype, including gene expression and epigenetics, as well as metabolomics. It also examines population genetics and evolutionary models and inference, with new chapters on the multi-species coalescent, admixture and ancient DNA, as well as genetic association studies including causal analyses and variant interpretation. The Handbook of Statistical Genomics focuses on explaining the main ideas, analysis methods and algorithms, citing key recent and historic literature for further details and references. It also includes a glossary of terms, acronyms and abbreviations, and features extensive cross-referencing between chapters, tying the different areas together. With heavy use of up-to-date examples and references to web-based resources, this continues to be a must-have reference in a vital area of research. Provides much-needed, timely coverage of new developments in this expanding area of study Numerous, brand new chapters, for example covering bacterial genomics, microbiome and metagenomics Detailed coverage of application areas, with chapters on plant breeding, conservation and forensic genetics Extensive coverage of human genetic epidemiology, including ethical aspects Edited by one of the leading experts in the field along with rising stars as his co-editors Chapter authors are world-renowned experts in the field, and newly emerging leaders. The Handbook of Statistical Genomics is an excellent introductory text for advanced graduate students and early-career researchers involved in statistical genetics.
The Statistics Of Gene Mapping
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Author : David Siegmund
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-27
The Statistics Of Gene Mapping written by David Siegmund and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-05-27 with Medical categories.
This book details the statistical concepts used in gene mapping, first in the experimental context of crosses of inbred lines and then in outbred populations, primarily humans. It presents elementary principles of probability and statistics, which are implemented by computational tools based on the R programming language to simulate genetic experiments and evaluate statistical analyses. Each chapter contains exercises, both theoretical and computational, some routine and others that are more challenging. The R programming language is developed in the text.