Modern Issues and Methods in Biostatistics

Author: Mark Chang
Publisher: Springer Science & Business Media
ISBN: 9781441998422
Format: PDF, Docs
Download Now
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.

Statistical Methods for Biostatistics and Related Fields

Author: Wolfgang Härdle
Publisher: Springer Science & Business Media
ISBN: 354032691X
Format: PDF, Mobi
Download Now
This book covers a wide range of recent statistical methods that are of interest to scientists in biostatistics as well as in other related fields such as chemometrics, environmetrics and geophysics. The contributed papers, from internationally recognized researchers, present various statistical methodologies together with a selected scope of their main mathematical properties and their application in a real case study.

The Fundamentals of Modern Statistical Genetics

Author: Nan M. Laird
Publisher: Springer Science & Business Media
ISBN: 9781441973382
Format: PDF, ePub, Mobi
Download Now
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.

Likelihood Bayesian and MCMC Methods in Quantitative Genetics

Author: Daniel Sorensen
Publisher: Springer Science & Business Media
ISBN: 0387954406
Format: PDF, Mobi
Download Now
This book, suitable for numerate biologists and for applied statisticians, provides the foundations of likelihood, Bayesian and MCMC methods in the context of genetic analysis of quantitative traits. Although a number of excellent texts in these areas have become available in recent years, the basic ideas and tools are typically described in a technically demanding style and contain much more detail than necessary. Here, an effort has been made to relate biological to statistical parameters throughout, and the book includes extensive examples that illustrate the developing argument.

Statistical Methods in Molecular Evolution

Author: Rasmus Nielsen
Publisher: Springer Science & Business Media
ISBN: 0387277331
Format: PDF, Docs
Download Now
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

Bayesian Methods in Structural Bioinformatics

Author: Thomas Hamelryck
Publisher: Springer
ISBN: 3642272258
Format: PDF, ePub, Docs
Download Now
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.

Principles of Biostatistics Second Edition

Author: Marcello Pagano
Publisher: CRC Press
ISBN: 0429952465
Format: PDF, Docs
Download Now
This edition is a reprint of the second edition published in 2000 by Brooks/Cole and then Cengage Learning. Principles of Biostatistics is aimed at students in the biological and health sciences who wish to learn modern research methods. It is based on a required course offered at the Harvard School of Public Health. In addition to these graduate students, many health professionals from the Harvard medical area attend as well. The book is divided into three parts. The first five chapters deal with collections of numbers and ways in which to summarize, explore, and explain them. The next two chapters focus on probability and introduce the tools needed for the subsequent investigation of uncertainty. It is only in the eighth chapter and thereafter that the authors distinguish between populations and samples and begin to investigate the inherent variability introduced by sampling, thus progressing to inference. Postponing the slightly more difficult concepts until a solid foundation has been established makes it easier for the reader to comprehend them. The supplements include a manual for students with solutions for odd-numbered exercises, a manual for instructors with solutions to all exercises, and selected data sets. Marcello Pagano is Professor of Statistical Computing in the Department of Biostatistics at the Harvard School of Public Health. His research in biostatistics is on computer intensive inference and surveillance methods that involve screening methodologies, with their associated laboratory tests, and in obtaining more accurate testing results that use existing technologies. Kimberlee Gauvreau is Associate Professor in the Department of Biostatistics and Associate Professor of Pediatrics at Harvard Medical School. Dr. Gauvreau’s research focuses on biostatistical issues arising in the field of pediatric cardiology. She also works on the development and validation of methods of adjustment for case mix complexity.

Methods and Applications of Statistics in the Life and Health Sciences

Author: N. Balakrishnan
Publisher: John Wiley & Sons
ISBN: 0470405090
Format: PDF, Mobi
Download Now
"Data collection holds an essential part in dictating the future of health sciences and public health, as the compilation of statistics allows researchers and medical practitioners to monitor trends in health status, identify health problems, and evaluate the impact of health policies and programs. Methods and Applications of Statistics in the Life and Health Sciences serves as a single, one-of-a-kind resource on the wide range of statistical methods, techniques, and applications that are applied in modern life and health sciences in research. Specially designed to present encyclopedic content in an accessible and self-contained format, this book outlines thorough coverage of the underlying theory and standard applications to research in related disciplines such as biology, epidemiology, clinical trials, and public health. Uniquely combining established literature with cutting-edge research, this book contains classical works and more than twenty-five new articles and completely revised contributions from the acclaimed Encyclopedia of Statistical Sciences, Second Edition. The result is a compilation of more than eighty articles that explores classic methodology and new topics."--Publisher's description.

Applied Biostatistics for the Health Sciences

Author: Richard J. Rossi
Publisher: John Wiley & Sons
ISBN: 0470147644
Format: PDF, Mobi
Download Now
Biostatistics is quickly becoming one of the most important areas of statistics due to the tremendous increase in health care needs. This book successfully introduces the terminology, concepts, and correct uses and interpretation of biostatistics. It is ideal for practitioners as well as students going into health care fields. Pedagogical features include formulas highlighted in text boxes and chapter summaries that highlight key vocabulary and concepts for the chapter. An accompanying Web site provides both MINITAB® and Microsoft® Office Excel® data files data for the case studies and exercises that are contained in the text.

Research Methodology In Plant Science

Author: P.S. Narayana
Publisher: Scientific Publishers
ISBN: 9387307670
Format: PDF, ePub, Mobi
Download Now
The book comprises of different chapters associated with methodology in Plant science (Botany), describing in a simple and comprehensive way. The importance of creativity and motivation in research, the planning and proposal of research project, the description of different techniques involved in research are described in an elaborate way. It also includes the sources/collection of scientific information, method of scientific report/paper/thesis writing etc. The book is also a source of different aspects of research methodology in plant science dealt with in a comprehensive manner tailored to the needs of postgraduate students/research scholars for easy understanding. The book is profusely illustrated. The different chapters described in the book include: Introduction, Microscopy, Plant micro-technique, Smear/Sqush technique, Plant tissue culture, Herbarium technique, Hydrogen ion concentration (pH), Centrifugation, Chromatography, Electrophoresis, Colorimetry, Spectro-photometry, Radio-isotopes in biology and Computers and their application in plant sciences. Chapters on Biostatistics, Biophysics and Bioinformatics have also been included to help the student in the statistical analysis of the results, physical principles involved in the operation of different instruments and basics of bioinformatics. We sincerely hope that this book helps to fill up the lacuna and provides what all that is needed about the research methods required for a scholar/student in plant sciences to pursue their higher studies.