Download or read book Modeling Dose Response Microarray Data in Early Drug Development Experiments Using R written by Dan Lin and published by Springer Science & Business Media. This book was released on 2012-08-27 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the analysis of dose-response microarray data in pharmaceutical settings, the goal being to cover this important topic for early drug development experiments and to provide user-friendly R packages that can be used to analyze this data. It is intended for biostatisticians and bioinformaticians in the pharmaceutical industry, biologists, and biostatistics/bioinformatics graduate students. Part I of the book is an introduction, in which we discuss the dose-response setting and the problem of estimating normal means under order restrictions. In particular, we discuss the pooled-adjacent-violator (PAV) algorithm and isotonic regression, as well as inference under order restrictions and non-linear parametric models, which are used in the second part of the book. Part II is the core of the book, in which we focus on the analysis of dose-response microarray data. Methodological topics discussed include: • Multiplicity adjustment • Test statistics and procedures for the analysis of dose-response microarray data • Resampling-based inference and use of the SAM method for small-variance genes in the data • Identification and classification of dose-response curve shapes • Clustering of order-restricted (but not necessarily monotone) dose-response profiles • Gene set analysis to facilitate the interpretation of microarray results • Hierarchical Bayesian models and Bayesian variable selection • Non-linear models for dose-response microarray data • Multiple contrast tests • Multiple confidence intervals for selected parameters adjusted for the false coverage-statement rate All methodological issues in the book are illustrated using real-world examples of dose-response microarray datasets from early drug development experiments.

Download or read book Statistics in Toxicology Using R written by Ludwig A. Hothorn and published by CRC Press. This book was released on 2016-01-13 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: The apparent contradiction between statistical significance and biological relevance has diminished the value of statistical methods as a whole in toxicology. Moreover, recommendations for statistical analysis are imprecise in most toxicological guidelines. Addressing these dilemmas, Statistics in Toxicology Using R explains the statistical analysi

Download or read book Exploration and Analysis of DNA Microarray and Other High Dimensional Data written by Dhammika Amaratunga and published by John Wiley & Sons. This book was released on 2014-01-27 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “...extremely well written...a comprehensive and up-to-date overview of this important field.” – Journal of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage of recent advancements in microarray data analysis. A cutting-edge guide, the Second Edition demonstrates various methodologies for analyzing data in biomedical research and offers an overview of the modern techniques used in microarray technology to study patterns of gene activity. The new edition answers the need for an efficient outline of all phases of this revolutionary analytical technique, from preprocessing to the analysis stage. Utilizing research and experience from highly-qualified authors in fields of data analysis, Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition features: A new chapter on the interpretation of findings that includes a discussion of signatures and material on gene set analysis, including network analysis New topics of coverage including ABC clustering, biclustering, partial least squares, penalized methods, ensemble methods, and enriched ensemble methods Updated exercises to deepen knowledge of the presented material and provide readers with resources for further study The book is an ideal reference for scientists in biomedical and genomics research fields who analyze DNA microarrays and protein array data, as well as statisticians and bioinformatics practitioners. Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.

Download or read book Applied Biclustering Methods for Big and High Dimensional Data Using R written by Adetayo Kasim and published by CRC Press. This book was released on 2016-10-03 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proven Methods for Big Data Analysis As big data has become standard in many application areas, challenges have arisen related to methodology and software development, including how to discover meaningful patterns in the vast amounts of data. Addressing these problems, Applied Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix. The book presents an overview of data analysis using biclustering methods from a practical point of view. Real case studies in drug discovery, genetics, marketing research, biology, toxicity, and sports illustrate the use of several biclustering methods. References to technical details of the methods are provided for readers who wish to investigate the full theoretical background. All the methods are accompanied with R examples that show how to conduct the analyses. The examples, software, and other materials are available on a supplementary website.

Download or read book Applied Survival Analysis Using R written by Dirk F. Moore and published by Springer. This book was released on 2016-05-11 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical trials, epidemiological studies, and studies of animals. Many survival methods are extensions of techniques used in linear regression and categorical data, while other aspects of this field are unique to survival data. This text employs numerous actual examples to illustrate survival curve estimation, comparison of survivals of different groups, proper accounting for censoring and truncation, model variable selection, and residual analysis. Because explaining survival analysis requires more advanced mathematics than many other statistical topics, this book is organized with basic concepts and most frequently used procedures covered in earlier chapters, with more advanced topics near the end and in the appendices. A background in basic linear regression and categorical data analysis, as well as a basic knowledge of calculus and the R system, will help the reader to fully appreciate the information presented. Examples are simple and straightforward while still illustrating key points, shedding light on the application of survival analysis in a way that is useful for graduate students, researchers, and practitioners in biostatistics.

Download or read book Data Wrangling with R written by Bradley C. Boehmke, Ph.D. and published by Springer. This book was released on 2016-11-17 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques. This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned: How to work with different types of data such as numerics, characters, regular expressions, factors, and dates The difference between different data structures and how to create, add additional components to, and subset each data structure How to acquire and parse data from locations previously inaccessible How to develop functions and use loop control structures to reduce code redundancy How to use pipe operators to simplify code and make it more readable How to reshape the layout of data and manipulate, summarize, and join data sets

Download or read book Bayesian Cost Effectiveness Analysis with the R package BCEA written by Gianluca Baio and published by Springer. This book was released on 2017-05-25 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a description of the process of health economic evaluation and modelling for cost-effectiveness analysis, particularly from the perspective of a Bayesian statistical approach. Some relevant theory and introductory concepts are presented using practical examples and two running case studies. The book also describes in detail how to perform health economic evaluations using the R package BCEA (Bayesian Cost-Effectiveness Analysis). BCEA can be used to post-process the results of a Bayesian cost-effectiveness model and perform advanced analyses producing standardised and highly customisable outputs. It presents all the features of the package, including its many functions and their practical application, as well as its user-friendly web interface. The book is a valuable resource for statisticians and practitioners working in the field of health economics wanting to simplify and standardise their workflow, for example in the preparation of dossiers in support of marketing authorisation, or academic and scientific publications.

Download or read book Heart Rate Variability Analysis with the R package RHRV written by Constantino Antonio García Martínez and published by Springer. This book was released on 2017-09-18 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces readers to the basic concepts of Heart Rate Variability (HRV) and its most important analysis algorithms using a hands-on approach based on the open-source RHRV software. HRV refers to the variation over time of the intervals between consecutive heartbeats. Despite its apparent simplicity, HRV is one of the most important markers of the autonomic nervous system activity and it has been recognized as a useful predictor of several pathologies. The book discusses all the basic HRV topics, including the physiological contributions to HRV, clinical applications, HRV data acquisition, HRV data manipulation and HRV analysis using time-domain, frequency-domain, time-frequency, nonlinear and fractal techniques. Detailed examples based on real data sets are provided throughout the book to illustrate the algorithms and discuss the physiological implications of the results. Offering a comprehensive guide to analyzing beat information with RHRV, the book is intended for masters and Ph.D. students in various disciplines such as biomedical engineering, human and veterinary medicine, biology, and pharmacy, as well as researchers conducting heart rate variability analyses on both human and animal data.

Download or read book Dose Response Analysis Using R written by Christian Ritz and published by CRC Press. This book was released on 2019-07-19 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nowadays the term dose-response is used in many different contexts and many different scientific disciplines including agriculture, biochemistry, chemistry, environmental sciences, genetics, pharmacology, plant sciences, toxicology, and zoology. In the 1940 and 1950s, dose-response analysis was intimately linked to evaluation of toxicity in terms of binary responses, such as immobility and mortality, with a limited number of doses of a toxic compound being compared to a control group (dose 0). Later, dose-response analysis has been extended to other types of data and to more complex experimental designs. Moreover, estimation of model parameters has undergone a dramatic change, from struggling with cumbersome manual operations and transformations with pen and paper to rapid calculations on any laptop. Advances in statistical software have fueled this development. Key Features: Provides a practical and comprehensive overview of dose-response analysis. Includes numerous real data examples to illustrate the methodology. R code is integrated into the text to give guidance on applying the methods. Written with minimal mathematics to be suitable for practitioners. Includes code and datasets on the book’s GitHub: https://github.com/DoseResponse. This book focuses on estimation and interpretation of entirely parametric nonlinear dose-response models using the powerful statistical environment R. Specifically, this book introduces dose-response analysis of continuous, binomial, count, multinomial, and event-time dose-response data. The statistical models used are partly special cases, partly extensions of nonlinear regression models, generalized linear and nonlinear regression models, and nonlinear mixed-effects models (for hierarchical dose-response data). Both simple and complex dose-response experiments will be analyzed.

Download or read book ggplot2 written by Hadley Wickham and published by Springer. This book was released on 2016-06-08 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition to the classic book by ggplot2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggplot2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggplot2, it's easy to: produce handsome, publication-quality plots with automatic legends created from the plot specification superimpose multiple layers (points, lines, maps, tiles, box plots) from different data sources with automatically adjusted common scales add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression save any ggplot2 plot (or part thereof) for later modification or reuse create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple plots approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggplot2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page.

Download or read book Pulsed Electric Fields in Biotechnology written by Saša Haberl Meglič and published by Frontiers Media SA. This book was released on 2021-06-17 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Science and Decisions written by National Research Council and published by National Academies Press. This book was released on 2009-03-24 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Risk assessment has become a dominant public policy tool for making choices, based on limited resources, to protect public health and the environment. It has been instrumental to the mission of the U.S. Environmental Protection Agency (EPA) as well as other federal agencies in evaluating public health concerns, informing regulatory and technological decisions, prioritizing research needs and funding, and in developing approaches for cost-benefit analysis. However, risk assessment is at a crossroads. Despite advances in the field, risk assessment faces a number of significant challenges including lengthy delays in making complex decisions; lack of data leading to significant uncertainty in risk assessments; and many chemicals in the marketplace that have not been evaluated and emerging agents requiring assessment. Science and Decisions makes practical scientific and technical recommendations to address these challenges. This book is a complement to the widely used 1983 National Academies book, Risk Assessment in the Federal Government (also known as the Red Book). The earlier book established a framework for the concepts and conduct of risk assessment that has been adopted by numerous expert committees, regulatory agencies, and public health institutions. The new book embeds these concepts within a broader framework for risk-based decision-making. Together, these are essential references for those working in the regulatory and public health fields.

Download or read book Applications of Toxicogenomics in Safety Evaluation and Risk Assessment written by Darrell R. Boverhof and published by John Wiley & Sons. This book was released on 2011-10-11 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a timely overview of toxicogenomics, with special emphasis on the practical applications of this technology to the risk assessment process. Introductory sections are followed by a series of chapters highlighting practical and systematic applications of toxicogenomics in informing the risk assessment process – including the areas of mutagenicity, carcinogenicity, endocrine toxicity, organ-specific toxicity, population monitoring, and ecotoxicology. The book concludes with approaches for the integration of this technology in safety evaluation studies, and an outlook on how toxicogenomics and complementary technologies can reframe the current risk assessment paradigm.

Download or read book Encyclopedia of Biopharmaceutical Statistics Four Volume Set written by Shein-Chung Chow and published by CRC Press. This book was released on 2018-09-03 with total page 2434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines. This encyclopedia (1) provides a comprehensive and unified presentation of designs and analyses used at different stages of the drug development process, (2) gives a well-balanced summary of current regulatory requirements, and (3) describes recently developed statistical methods in the pharmaceutical sciences. Features of the Fourth Edition: 1. 78 new and revised entries have been added for a total of 308 chapters and a fourth volume has been added to encompass the increased number of chapters. 2. Revised and updated entries reflect changes and recent developments in regulatory requirements for the drug review/approval process and statistical designs and methodologies. 3. Additional topics include multiple-stage adaptive trial design in clinical research, translational medicine, design and analysis of biosimilar drug development, big data analytics, and real world evidence for clinical research and development. 4. A table of contents organized by stages of biopharmaceutical development provides easy access to relevant topics. About the Editor: Shein-Chung Chow, Ph.D. is currently an Associate Director, Office of Biostatistics, U.S. Food and Drug Administration (FDA). Dr. Chow is an Adjunct Professor at Duke University School of Medicine, as well as Adjunct Professor at Duke-NUS, Singapore and North Carolina State University. Dr. Chow is the Editor-in-Chief of the Journal of Biopharmaceutical Statistics and the Chapman & Hall/CRC Biostatistics Book Series and the author of 28 books and over 300 methodology papers. He was elected Fellow of the American Statistical Association in 1995.

Download or read book Toxicogenomics Based Cellular Models written by Jos Kleinjans and published by Academic Press. This book was released on 2014-01-02 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Toxicogenomics-Based Cellular Models is a unique and valuable reference for all academic and professional researchers employing toxicogenomic methods with respect to animal testing for chemical safety. This resource offers cutting-edge information on the application of toxicogenomics to developing alternatives to current animal toxicity tests. By illustrating the development of toxicogenomics-based cellular models for critical endpoints of toxicity and providing real-world examples for validation and data analysis, this book provides an assessment of the current state of the field, as well as opportunities and challenges for the future. Written by renowned international toxicological experts, this book explores ‘omics technology for developing new assays for toxicity testing and safety assessment and provides the reader with a focused examination of alternative means to animal testing. Describes the state-of-the-art in developing toxicogenomics-based cellular models for chemical-induced carcinogenicity, immunotoxicity, developmental toxicity, neurotoxicity and reproduction toxicity Illustrates how to validate toxicogenomics-based alternative test models and provides an outlook to societal and economic implementation of these novel assays Includes an overview of current testing methods and risk assessment frameworks Provides a real-world assessment by articulating the current development and challenges in toxicogenomics while suggesting ways to move this field forward

Download or read book Genomic Biomarkers for Pharmaceutical Development written by Yihong Yao and published by Academic Press. This book was released on 2013-07-16 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic Biomarkers for Pharmaceutical Development: Advancing Personalized Health Care provides an in-depth review of the state of translational science across all stages of pharmaceutical development with a special focus on personalized health care. This book provides a complete picture of biomarker development and validation in a pharmaceutical setting while addressing the inherent challenges of targeting the appropriate indications, biomarker robustness, regulatory hurdles, commercialization and much more. It features case studies devoted to the applications of pharmacogenomics, toxicogenomics, and other genetic technologies as they support drug discovery and development. With chapters written by international authorities in industry and academia, this work is a truly unique presentation of the thoughts and approaches that lead to the development of personalized medicine. Intended for all those involved in clinical translational research, this book is the ideal resource for scientists searching for the applications, strategies and successful approaches of translational science in pharmaceutical development. Provides case studies in applications of pharmacodynamic and predictive markers in drug development in oncology, autoimmunity, respiratory diseases and infectious diseases Shows how to identify potential new therapeutic targets in different diseases and provides examples of potential new disease indications for life cycle management of drugs Authored by leading international experts from industry and academia

Download or read book Innovative Statistics in Regulatory Science written by Shein-Chung Chow and published by CRC Press. This book was released on 2019-11-14 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical methods that are commonly used in the review and approval process of regulatory submissions are usually referred to as statistics in regulatory science or regulatory statistics. In a broader sense, statistics in regulatory science can be defined as valid statistics that are employed in the review and approval process of regulatory submissions of pharmaceutical products. In addition, statistics in regulatory science are involved with the development of regulatory policy, guidance, and regulatory critical clinical initiatives related research. This book is devoted to the discussion of statistics in regulatory science for pharmaceutical development. It covers practical issues that are commonly encountered in regulatory science of pharmaceutical research and development including topics related to research activities, review of regulatory submissions, recent critical clinical initiatives, and policy/guidance development in regulatory science. Devoted entirely to discussing statistics in regulatory science for pharmaceutical development. Reviews critical issues (e.g., endpoint/margin selection and complex innovative design such as adaptive trial design) in the pharmaceutical development and regulatory approval process. Clarifies controversial statistical issues (e.g., hypothesis testing versus confidence interval approach, missing data/estimands, multiplicity, and Bayesian design and approach) in review/approval of regulatory submissions. Proposes innovative thinking regarding study designs and statistical methods (e.g., n-of-1 trial design, adaptive trial design, and probability monitoring procedure for sample size) for rare disease drug development. Provides insight regarding current regulatory clinical initiatives (e.g., precision/personalized medicine, biomarker-driven target clinical trials, model informed drug development, big data analytics, and real world data/evidence). This book provides key statistical concepts, innovative designs, and analysis methods that are useful in regulatory science. Also included are some practical, challenging, and controversial issues that are commonly seen in the review and approval process of regulatory submissions. About the author Shein-Chung Chow, Ph.D. is currently a Professor at Duke University School of Medicine, Durham, NC. He was previously the Associate Director at the Office of Biostatistics, Center for Drug Evaluation and Research, United States Food and Drug Administration (FDA). Dr. Chow has also held various positions in the pharmaceutical industry such as Vice President at Millennium, Cambridge, MA, Executive Director at Covance, Princeton, NJ, and Director and Department Head at Bristol-Myers Squibb, Plainsboro, NJ. He was elected Fellow of the American Statistical Association and an elected member of the ISI (International Statistical Institute). Dr. Chow is Editor-in-Chief of the Journal of Biopharmaceutical Statistics and Biostatistics Book Series, Chapman and Hall/CRC Press, Taylor & Francis, New York. Dr. Chow is the author or co-author of over 300 methodology papers and 30 books.