Mathematical And Statistical Methods For Genetic Analysis

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Mathematical And Statistical Methods For Genetic Analysis

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Author : Kenneth Lange
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Mathematical And Statistical Methods For Genetic Analysis written by Kenneth Lange 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 2013-04-17 with Mathematics categories.

During the past decade, geneticists have constructed detailed maps of the human genome and cloned scores of Mendelian disease genes. They 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 will transform medicine and agriculture. This revolution depends vitally on the contributions of applied mathematicians, statisticians, and computer scientists. Mathematical and Statistical Methods for Genetic Analysis is written to equip 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 includes many topics currently accessible only in journal articles, including pedigree analysis algorithms, Markov chain Monte Carlo methods, reconstruction of evolutionary trees, radiation hybrid mapping, and models of recombination. Exercise sets are included. Kenneth Lange is Professor of Biostatistics and Mathematics and the Pharmacia & Upjohn Foundations Research Professor at the University of Michigan. He has held visiting appointments at MIT and Harvard. His research interests include human genetics, population modeling, biomedical imaging, computational statistics, and applied stochastic processes.

Mathematical And Statistical Methods For Genetic Analysis 2e

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Author : Lange
language : en
Publisher:
Release Date : 2004-01-01

Mathematical And Statistical Methods For Genetic Analysis 2e written by Lange and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-01-01 with categories.

Introduction To Statistical Methods In Modern Genetics

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Author : M.C. Yang
language : en
Publisher: CRC Press
Release Date : 2000-02-23

Introduction To Statistical Methods In Modern Genetics written by M.C. Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-02-23 with Mathematics categories.

Though the basic statistical theory behind modern genetics is not that difficult, most statistical genetics papers are not easy to read for beginners, and fitting formulae to a particular area of application quickly becomes very tedious. Introduction to Statistical Methods in Modern Genetics makes a clear distinction between the necessary and unnecessary complexities. The author keeps the derivations of methods simple without losing the mathematical details. He also provides the necessary background in modern genetics for newcomers to the field, including discussion ranging from biological and molecular experiments to gene hunting and genetic engineering.

Biometrics Volume Ii

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Author : Susan R. Wilson
language : en
Publisher: EOLSS Publications
Release Date : 2009-02-18

Biometrics Volume Ii written by Susan R. Wilson and has been published by EOLSS Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-18 with Mathematics categories.

Biometrics is a component of Encyclopedia of Mathematical Sciences in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Biometry is a broad discipline covering all applications of statistics and mathematics to biology. The Theme Biometrics is divided into areas of expertise essential for a proper application of statistical and mathematical methods to contemporary biological problems. These volumes cover four main topics: Data Collection and Analysis, Statistical Methodology, Computation, Biostatistical Methods and Research Design and Selected Topics. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers and NGOs.

Optimization

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Author : Kenneth Lange
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Optimization written by Kenneth Lange 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 2013-03-09 with Mathematics categories.

Finite-dimensional optimization problems occur throughout the mathematical sciences. The majority of these problems cannot be solved analytically. This introduction to optimization attempts to strike a balance between presentation of mathematical theory and development of numerical algorithms. Building on students’ skills in calculus and linear algebra, the text provides a rigorous exposition without undue abstraction. Its stress on convexity serves as bridge between linear and nonlinear programming and makes it possible to give a modern exposition of linear programming based on the interior point method rather than the simplex method. The emphasis on statistical applications will be especially appealing to graduate students of statistics and biostatistics. The intended audience also includes graduate students in applied mathematics, computational biology, computer science, economics, and physics as well as upper division undergraduate majors in mathematics who want to see rigorous mathematics combined with real applications. Chapter 1 reviews classical methods for the exact solution of optimization problems. Chapters 2 and 3 summarize relevant concepts from mathematical analysis. Chapter 4 presents the Karush-Kuhn-Tucker conditions for optimal points in constrained nonlinear programming. Chapter 5 discusses convexity and its implications in optimization. Chapters 6 and 7 introduce the MM and the EM algorithms widely used in statistics. Chapters 8 and 9 discuss Newton’s method and its offshoots, quasi-Newton algorithms and the method of conjugate gradients. Chapter 10 summarizes convergence results, and Chapter 11 briefly surveys convex programming, duality, and Dykstra’s algorithm. From the reviews: "...An excellent, imaginative, and authoritative text on the difficult topic of modeling the problems of multivariate outcomes with different scaling levels, different units of analysis, and differentstudy designs simultaneously." Biometrics, March 2005 "...As a textbook, Optimization does provide a valuable introduction to an important branch of applicable mathematics." Technometrics, August 2005 "...I found Optimization to be an extremely engaging textbook....the text is ideal for graduate students or researchers beginning research on optimization problems in statistics. There is little doubt that someone who worked through the text as part of a reading course or specialized graduate seminar would benefit greatly from the author's perspective..." Journal of the American Statistical Association, December 2005

Using The Biological Literature

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Author : Diane Schmidt
language : en
Publisher: CRC Press
Release Date : 2014-04-14

Using The Biological Literature written by Diane Schmidt and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-14 with Language Arts & Disciplines categories.

The biological sciences cover a broad array of literature types, from younger fields like molecular biology with its reliance on recent journal articles, genomic databases, and protocol manuals to classic fields such as taxonomy with its scattered literature found in monographs and journals from the past three centuries. Using the Biological Literature: A Practical Guide, Fourth Edition is an annotated guide to selected resources in the biological sciences, presenting a wide-ranging list of important sources. This completely revised edition contains numerous new resources and descriptions of all entries including textbooks. The guide emphasizes current materials in the English language and includes retrospective references for historical perspective and to provide access to the taxonomic literature. It covers both print and electronic resources including monographs, journals, databases, indexes and abstracting tools, websites, and associations—providing users with listings of authoritative informational resources of both classical and recently published works. With chapters devoted to each of the main fields in the basic biological sciences, this book offers a guide to the best and most up-to-date resources in biology. It is appropriate for anyone interested in searching the biological literature, from undergraduate students to faculty, researchers, and librarians. The guide includes a supplementary website dedicated to keeping URLs of electronic and web-based resources up to date, a popular feature continued from the third edition.

Statistical Genetics Of Quantitative Traits

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Author : Rongling Wu
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-17

Statistical Genetics Of Quantitative Traits written by Rongling Wu 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 2007-07-17 with Science categories.

Most traits in nature and of importance to agriculture are quantitatively inherited. These traits are di?cult to study due to the complex nature of their inheritance. However, recent developments of genomic technologies provide a revolutionary means for unraveling the secrets of genetic variation in quantitative traits. Genomic te- nologies allow the molecular characterization of polymorphic markers throughout the entire genome that are then used to identify and map the genes or quantitative trait loci (QTLs) underlying a quantitative trait based on linkage analysis. Statistical analysis is a crucial tool for analyzing genome data, which are now becoming increasingly available for a variety of species, and for giving precise exp- nations regarding genetic variation in quantitative traits occurring among species, populations, families, and individuals. In 1989, Lander and Botstein published a ha- mark methodological paper for interval mapping that enables geneticists to detect and estimate individual QTL that control the phenotype of a trait. Today, interval mappingisanimportantstatisticaltoolforstudyingthegeneticsofquantitativetraits at the molecular level, and has led to the discovery of thousands of QTLs responsible for a variety of traits in plants, animals, and humans. In a recent study published in Science, Li, Zhou, and Sang (2006, 311, 1936–1939) were able to characterize the molecular basis of the reduction of grain shattering – a fundamental selection process for rice domestication – at the detected QTL by interval mapping.

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.

Unified Methods For Censored Longitudinal Data And Causality

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Author : Mark J. van der Laan
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-11-12

Unified Methods For Censored Longitudinal Data And Causality written by Mark J. van der Laan 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 2012-11-12 with Mathematics categories.

During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics among many others, which involve collection of large amounts of data on subjects or organisms over time. The goal of such studies can be formulated as estimation of a finite dimensional parameter of the population distribution corresponding to the observed time- dependent process. Such estimation problems arise in survival analysis, causal inference and regression analysis. This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative censoring and treatment assignment in so called semiparametric models. Semiparametric models are particularly attractive since they allow the presence of large unmodeled nuisance parameters. These techniques include estimation of regression parameters in the familiar (multivariate) generalized linear regression and multiplicative intensity models. They go beyond standard statistical approaches by incorporating all the observed data to allow for informative censoring, to obtain maximal efficiency, and by developing estimators of causal effects. It can be used to teach masters and Ph.D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.

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.