A Guide To Qtl Mapping With R Qtl
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A Guide To Qtl Mapping With R Qtl
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Author : Karl W. Broman
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-07-21
A Guide To Qtl Mapping With R Qtl written by Karl W. Broman 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 2009-07-21 with Science categories.
Comprehensive discussion of QTL mapping concepts and theory Detailed instructions on the use of the R/qtl software, the most featured and flexible software for QTL mapping Two case studies illustrate QTL analysis in its entirety
Statistical Genomics
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Author : Ben Hui Liu
language : en
Publisher: CRC Press
Release Date : 2017-11-22
Statistical Genomics written by Ben Hui Liu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-22 with Mathematics categories.
Genomics, the mapping of the entire genetic complement of an organism, is the new frontier in biology. This handbook on the statistical issues of genomics covers current methods and the tried-and-true classical approaches.
Genetic Mapping And Marker Assisted Selection
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Author : N. Manikanda Boopathi
language : en
Publisher: Springer Nature
Release Date : 2020-04-07
Genetic Mapping And Marker Assisted Selection written by N. Manikanda Boopathi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-07 with Medical categories.
The first edition of this book, Genetic Mapping and Marker Assisted Selection: Basics, Practice and Benefits, was widely appreciated as the first of its kind on this topic and has been listed as a reference work in several agricultural universities’ curricula. A great deal has happened over the last five years, making it high time to incorporate recent developments in genetic mapping and report on novel strategies in marker assisted selection in crop plants as a second edition. This book addresses a range of topics, including: new marker types and their genotyping methods based on high-throughput technologies, advances in genomics and their role in new marker development, improvements in genetic mapping strategies and software updates, developments in phenomics and their applications in QTL mapping, and how to incorporate these developments and advances in marker assisted selection in crop plants. Similar to the first edition, each technique and method is explained using a step-by-step method, allowing the book to serve as a self-study guide for scholars whose work involves the genetic improvement of crop plants for any trait of interest, particularly for biotic and abiotic stress resistance. In addition, the book offers a valuable guide for undergraduate and graduate students at agricultural universities and institutes that are interested and/or involved in the genetic improvement of crop plants using modern tools. In addition, the bibliography includes a list of suggested works for pursuing further research on the topics covered.
Modern Issues And Methods In Biostatistics
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Author : Mark Chang
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-07-15
Modern Issues And Methods In Biostatistics written by Mark Chang 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 2011-07-15 with Medical categories.
Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.
Applied Data Science
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Author : Martin Braschler
language : en
Publisher: Springer
Release Date : 2019-06-13
Applied Data Science written by Martin Braschler and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-13 with Computers categories.
This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.
Bayesian Methods In Structural Bioinformatics
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Author : Thomas Hamelryck
language : en
Publisher: Springer
Release Date : 2012-03-23
Bayesian Methods In Structural Bioinformatics written by Thomas Hamelryck and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-23 with Medical categories.
This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.
Analyzing Ecological Data
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Author : Alain Zuur
language : en
Publisher: Springer
Release Date : 2007-08-29
Analyzing Ecological Data written by Alain Zuur and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-29 with Science categories.
This book provides a practical introduction to analyzing ecological data using real data sets. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader’s own data analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.
Statistical Methods In Bioinformatics
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Author : Warren J. Ewens
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-09-30
Statistical Methods In Bioinformatics written by Warren J. Ewens 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 2005-09-30 with Science categories.
Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community. This book provides an introduction to some of these new methods. The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes. The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods. The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized. The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science. Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999. Comments on the first edition: "This book would be an ideal text for a postgraduate course...[and] is equally well suited to individual study.... I would recommend the book highly." (Biometrics) "Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces." (Naturwissenschaften) "The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details." (Journal American Statistical Association) "The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book." (Metrika)
The Frailty Model
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Author : Luc Duchateau
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-23
The Frailty Model written by Luc Duchateau 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 2007-10-23 with Mathematics categories.
Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.
Eqtl Analysis
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Author : Xinghua Mindy Shi
language : en
Publisher: Humana
Release Date : 2021-01-02
Eqtl Analysis written by Xinghua Mindy Shi and has been published by Humana this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-02 with Science categories.
This volume details state-of-art eQTL analysis, where interdisciplinary researchers are provided both theoretical and practical guidance to eQTL analysis and interpretation. Chapters guide readers through methods and tools for eQTL and QTL analysis and the usage of such analysis in various scenarios. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, eQTL Analysis: Methods and Protocols to ensure successful results in the further study of this vital field.