Download or read book Mathematical and Statistical Methods for Genetic Analysis written by Kenneth Lange and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book A Statistical Approach to Genetic Epidemiology written by Andreas Ziegler and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Statistical Approach to Genetic Epidemiology After studying statistics and mathematics at the University of Munich and obtaining his doctoral degree from the University of Dortmund, Andreas Ziegler received the Johann-Peter-Süssmilch-Medal of the German Association for Medical Informatics, Biometry and Epidemiology for his post-doctoral work on “Model Free Linkage Analysis of Quantitative Traits” in 1999. In 2004, he was one of the recipients of the Fritz-Linder-Forum-Award from the German Association for Surgery.
Download or read book Mathematical And Statistical Methods For Genetic Analysis 2E written by Lange and published by . This book was released on 2004-01-01 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Methods in Bioinformatics written by Warren J. Ewens and published by Springer Science & Business Media. This book was released on 2005-09-30 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)
Download or read book Handbook of Statistical Genetics written by David J. Balding and published by John Wiley & Sons. This book was released on 2008-06-10 with total page 1616 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Statistical Genetics written by Benjamin Neale and published by Garland Science. This book was released on 2007-11-30 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Genetics is an advanced textbook focusing on conducting genome-wide linkage and association analysis in order to identify the genes responsible for complex behaviors and diseases. Starting with an introductory section on statistics and quantitative genetics, it covers both established and new methodologies, providing the genetic and statistical theory on which they are based. Each chapter is written by leading researchers, who give the reader the benefit of their experience with worked examples, study design, and sources of error. The text can be used in conjunction with an associated website (www.genemapping.org) that provides supplementary material and links to downloadable software.
Download or read book Biometrics Volume II written by Susan R. Wilson and published by EOLSS Publications. This book was released on 2009-02-18 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Introduction to Statistical Methods in Modern Genetics written by M.C. Yang and published by CRC Press. This book was released on 2000-02-23 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Statistics of Gene Mapping written by David Siegmund and published by Springer Science & Business Media. This book was released on 2007-05-27 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Some Recent Advances In Mathematics And Statistics Proceedings Of Statistics 2011 Canada imst 2011 fim Xx written by Yogendra P Chaubey and published by World Scientific. This book was released on 2013-03-14 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume consists of a series of research papers presented at the conference Statistics 2011 Canada: 5th Canadian Conference in Applied Statistics held together with the 20th conference of the Forum for Interdisciplinary Mathematics titled, “Interdisciplinary Mathematical & Statistical Techniques”. These papers cover a wide range of topics from applications of Mathematics and Statistics such as Selection Bias in Surveys, Biomarker Discovery, Analysis of Earth Temperature, Supply Chain Management, Trimmed ANOVA, Zero-inflated Data, Non-Gaussian Time Series, and Stochastic Ordering; Classification, Nonparametric Test, and Jackknifed Ridge Estimator; Bayes Factor; Random Graphs and Error Correcting Codes; Meta Analysis; and National Health Plans and Risk Reduction through Supply Chain.The topics have been reviewed by experts in the field and the selected papers are expected to provide a topical resource on the subjects concerned.
Download or read book Molecular Evolution written by Ziheng Yang and published by Oxford University Press. This book was released on 2014 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods. The flood of genomic data has generated an acute need for powerful statistical methods and efficient computational algorithms to enable their effective analysis and interpretation. Molecular Evolution: a statistical approach presents and explains modern statistical methods and computational algorithms for the comparative analysis of genetic sequence data in the fields of molecular evolution, molecular phylogenetics, statistical phylogeography, and comparative genomics. Written by an expert in the field, the book emphasizes conceptual understanding rather than mathematical proofs. The text is enlivened with numerous examples of real data analysis and numerical calculations to illustrate the theory, in addition to the working problems at the end of each chapter. The coverage of maximum likelihood and Bayesian methods are in particular up-to-date, comprehensive, and authoritative. This advanced textbook is aimed at graduate level students and professional researchers (both empiricists and theoreticians) in the fields of bioinformatics and computational biology, statistical genomics, evolutionary biology, molecular systematics, and population genetics. It will also be of relevance and use to a wider audience of applied statisticians, mathematicians, and computer scientists working in computational biology.
Download or read book Foundations of Mathematical Genetics written by Anthony William Fairbank Edwards and published by Cambridge University Press. This book was released on 2000-01-13 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: A definitive account of the origins of modern mathematical population genetics, first published in 2000.
Download or read book Some Recent Advances in Mathematics and Statistics written by Yogendra P. Chaubey and published by World Scientific. This book was released on 2013 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume consists of a series of research papers presented at the conference Statistics 2011 Canada: 5th Canadian Conference in Applied Statistics held together with the 20th conference of the Forum for Interdisciplinary Mathematics titled, OC Interdisciplinary Mathematical & Statistical TechniquesOCO. These papers cover a wide range of topics from applications of Mathematics and Statistics such as Selection Bias in Surveys, Biomarker Discovery, Analysis of Earth Temperature, Supply Chain Management, Trimmed ANOVA, Zero-inflated Data, Non-Gaussian Time Series, and Stochastic Ordering; Classification, Nonparametric Test, and Jackknifed Ridge Estimator; Bayes Factor; Random Graphs and Error Correcting Codes; Meta Analysis; and National Health Plans and Risk Reduction through Supply Chain.The topics have been reviewed by experts in the field and the selected papers are expected to provide a topical resource on the subjects concerned.
Download or read book Exact Analysis of Discrete Data written by Karim F. Hirji and published by CRC Press. This book was released on 2005-11-18 with total page 1066 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers in fields ranging from biology and medicine to the social sciences, law, and economics regularly encounter variables that are discrete or categorical in nature. While there is no dearth of books on the analysis and interpretation of such data, these generally focus on large sample methods. When sample sizes are not large or the data are
Download or read book Optimization written by Kenneth Lange and published by Springer Science & Business Media. This book was released on 2004-06-17 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lange is a Springer author of other successful books. This is the first book that emphasizes the applications of optimization to statistics. The emphasis on statistical applications will be especially appealing to graduate students of statistics and biostatistics.
Download or read book Bioinformatics for Geneticists written by Michael R. Barnes and published by John Wiley & Sons. This book was released on 2003-07-01 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely book illustrates the value of bioinformatics, not simply as a set of tools but rather as a science increasingly essential to navigate and manage the host of information generated by genomics and the availability of completely sequenced genomes. Bioinformatics can be used at all stages of genetics research: to improve study design, to assist in candidate gene identification, to aid data interpretation and management and to shed light on the molecular pathology of disease-causing mutations. Written specifically for geneticists, this book explains the relevance of bioinformatics showing how it may be used to enhance genetic data mining and markedly improve genetic analysis.
Download or read book Advances in Genetic Statistics written by Basavarajaiah D M and published by Educreation Publishing. This book was released on with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many books on genetic statistics and quantitative genetics. These books expect different level of preparedness and analytical interventions emphasis on the formulation of real breeding data sets. This book is not introductory, it presumes various statistical and mathematical models demonstrated and derived considering by real breeding data sets. Reader are expected to know the essential of recent statistical tools such as sensor fusion estimation techniques, Kernel regression model, mathematical modeling on hardy Weinberg equilibrium, Pham kinetic genetic model, MLE's, OLR, weighted ordinary least square analysis, genetic correlation, heritability tested by advanced statistical tools, extraction of dummy variables from genetic and non-genetic components, random mating probability models, Risk analysis of human hereditary data by Bayesian approach, algorithms of sex linked inherited X-chromosomes, evaluation of pedigree through statistical approach, sex-linked recessive disorder of human population, data reduction techniques by snap shot techniques, Kal man filter estimation of multiple genetic traits, estimation of genetic variance, structural changes of genetic parameters, oscillation of genotypic and environmental variance, linear and nonlinear models etc. The main emphasis of the entire book is derivation of mathematical and statistical models to prove hardy Weinberg equilibrium at large random mating population. The present text book describes salient objectives and practical applicability to learn what methods are available and more importantly, when they should be applied in real life .Many examples are presented to clarify the use of the recent statistical techniques and to demonstrate what conclusions can be made at the right time modeling on genetics. Nevertheless, Statistical & mathematical modeling is a diversified area including many different topics illustrated by real breeding data sets. Furthermore, an advanced statistical technique has covered in the present edition. As per the genetic model formulation, a new technology is described in all the chapters. The PG students and research Scholars will easily extend the methods to enable for the compilation of high dimensional breeding datasets (Big data) generated from different experimental designs. Although the book narrowly focuses on a few topics, each topic Genetic fundamentals is provided with the partial derivatives. In collective terms, the statistical genetics is a multidisciplinary area with rapid developments, the present text book will helps to breeder's, researcher's and students to solve the real world problems of Genetics. For example, during the time between the completion of the first draft and the publication of this book, new methodologies and model formulation may have already been developed. Therefore, the book can only focus on the principles of advance statistical genetics. The present academic book intends to be used as a textbook for post graduate students in human, plant and animal genetics, but it can also be used by researchers as a reference book. For advanced readers, they can choose to read any particular chapters as they desire.