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Statistical Problems in Genetics and Molecular Biology

Statistical Problems in Genetics and Molecular Biology
Author: Norman R. Drinkwater
Publisher: Createspace Independent Publishing Platform
Total Pages: 298
Release: 2011-12-15
Genre: Medical
ISBN: 9781467957908

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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

Statistics in Human Genetics and Molecular Biology
Author: Cavan Reilly
Publisher: CRC Press
Total Pages: 284
Release: 2009-06-19
Genre: Mathematics
ISBN: 1420072641

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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

Handbook of Statistical Genetics
Author: D. J. Balding
Publisher:
Total Pages: 904
Release: 2001-03-28
Genre: Mathematics
ISBN:

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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.


The Fundamentals of Modern Statistical Genetics

The Fundamentals of Modern Statistical Genetics
Author: Nan M. Laird
Publisher: Springer Science & Business Media
Total Pages: 226
Release: 2010-12-13
Genre: Medical
ISBN: 1441973389

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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.


Statistical Methods in Molecular Evolution

Statistical Methods in Molecular Evolution
Author: Rasmus Nielsen
Publisher: Springer Science & Business Media
Total Pages: 503
Release: 2006-05-06
Genre: Science
ISBN: 0387277331

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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


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

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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.


Solving Problems in Genetics

Solving Problems in Genetics
Author: Richard Kowles
Publisher: Springer Science & Business Media
Total Pages: 489
Release: 2013-12-01
Genre: Medical
ISBN: 1461302056

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Helping undergraduates in the analysis of genetic problems, this work emphasizes solutions, not just answers. The strategy is to provide the student with the essential steps and the reasoning involved in conducting the analysis, and throughout the book, an attempt is made to present a balanced account of genetics. Topics, therefore, center about Mendelian, cytogenetic, molecular, quantitative, and population genetics, with a few more specialized areas. Whenever possible, the student is provided with the appropriate basic statistics necessary to make some the analyses. The book also builds on itself; that is, analytical methods learned in early parts of the book are subsequently revisited and used for later analyses. A deliberate attempt is made to make complex concepts simple, and sometimes to point out that apparently simple concepts are sometimes less so on further investigation. Any student taking a genetics course will find this an invaluable aid to achieving a good understanding of genetic principles and practice.


An Introduction to Statistical Genetic Data Analysis

An Introduction to Statistical Genetic Data Analysis
Author: Melinda C. Mills
Publisher: MIT Press
Total Pages: 433
Release: 2020-02-18
Genre: Science
ISBN: 0262538385

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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.


Statistical Methods in Molecular Biology

Statistical Methods in Molecular Biology
Author: Heejung Bang
Publisher: Humana
Total Pages: 636
Release: 2016-08-23
Genre: Science
ISBN: 9781493961245

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This progressive book presents the basic principles of proper statistical analyses. It progresses to more advanced statistical methods in response to rapidly developing technologies and methodologies in the field of molecular biology.


Parametric Statistical Change Point Analysis

Parametric Statistical Change Point Analysis
Author: Jie Chen
Publisher: Springer Science & Business Media
Total Pages: 282
Release: 2011-11-06
Genre: Mathematics
ISBN: 0817648011

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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.