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Exploration and Analysis of DNA Microarray and Other High-Dimensional Data (Hardcover, 2nd Edition): Dhammika Amaratunga,... Exploration and Analysis of DNA Microarray and Other High-Dimensional Data (Hardcover, 2nd Edition)
Dhammika Amaratunga, Javier Cabrera, Ziv Shkedy
R2,400 R1,690 Discovery Miles 16 900 Save R710 (30%) Shipped within 7 - 13 working days

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.

Applied Surrogate Endpoint Evaluation Methods with SAS and R (Hardcover): Ariel Alonso, Theophile Bigirumurame, Tomasz... Applied Surrogate Endpoint Evaluation Methods with SAS and R (Hardcover)
Ariel Alonso, Theophile Bigirumurame, Tomasz Burzykowski, Marc Buyse, Geert Molenberghs, …
R1,375 R1,286 Discovery Miles 12 860 Save R89 (6%) Shipped within 7 - 12 working days

An important factor that affects the duration, complexity and cost of a clinical trial is the endpoint used to study the treatment's efficacy. When a true endpoint is difficult to use because of such factors as long follow-up times or prohibitive cost, it is sometimes possible to use a surrogate endpoint that can be measured in a more convenient or cost-effective way. This book focuses on the use of surrogate endpoint evaluation methods in practice, using SAS and R.

Modeling Infectious Disease Parameters Based on Serological and Social Contact Data - A Modern Statistical Perspective... Modeling Infectious Disease Parameters Based on Serological and Social Contact Data - A Modern Statistical Perspective (Hardcover, 2012 ed.)
Niel Hens, Ziv Shkedy, Marc Aerts, Christel Faes, Pierre Van Damme, …
R2,441 R1,962 Discovery Miles 19 620 Save R479 (20%) Shipped within 7 - 12 working days

Mathematical epidemiology of infectious diseases usually involves describing the flow of individuals between mutually exclusive infection states. One of the key parameters describing the transition from the susceptible to the infected class is the hazard of infection, often referred to as the force of infection. The force of infection reflects the degree of contact with potential for transmission between infected and susceptible individuals. The mathematical relation between the force of infection and effective contact patterns is generally assumed to be subjected to the mass action principle, which yields the necessary information to estimate the basic reproduction number, another key parameter in infectious disease epidemiology. It is within this context that the Center for Statistics (CenStat, I-Biostat, Hasselt University) and the Centre for the Evaluation of Vaccination and the Centre for Health Economic Research and Modelling Infectious Diseases (CEV, CHERMID, Vaccine and Infectious Disease Institute, University of Antwerp) have collaborated over the past 15 years. This book demonstrates the past and current research activities of these institutes and can be considered to be a milestone in this collaboration. This book is focused on the application of modern statistical methods and models to estimate infectious disease parameters. We want to provide the readers with software guidance, such as R packages, and with data, as far as they can be made publicly available.

Applied Biclustering Methods for Big and High-Dimensional Data Using R (Hardcover): Adetayo Kasim, Ziv Shkedy, Sebastian... Applied Biclustering Methods for Big and High-Dimensional Data Using R (Hardcover)
Adetayo Kasim, Ziv Shkedy, Sebastian Kaiser, Sepp Hochreiter, Willem Talloen
R1,549 Discovery Miles 15 490 Shipped within 7 - 12 working days

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.

Modeling Infectious Disease Parameters Based on Serological and Social Contact Data - A Modern Statistical Perspective... Modeling Infectious Disease Parameters Based on Serological and Social Contact Data - A Modern Statistical Perspective (Paperback, 2012 ed.)
Niel Hens, Ziv Shkedy, Marc Aerts, Christel Faes, Pierre Van Damme, …
R2,214 R2,102 Discovery Miles 21 020 Save R112 (5%) Special order

Mathematical epidemiology of infectious diseases usually involves describing the flow of individuals between mutually exclusive infection states. One of the key parameters describing the transition from the susceptible to the infected class is the hazard of infection, often referred to as the force of infection. The force of infection reflects the degree of contact with potential for transmission between infected and susceptible individuals. The mathematical relation between the force of infection and effective contact patterns is generally assumed to be subjected to the mass action principle, which yields the necessary information to estimate the basic reproduction number, another key parameter in infectious disease epidemiology. It is within this context that the Center for Statistics (CenStat, I-Biostat, Hasselt University) and the Centre for the Evaluation of Vaccination and the Centre for Health Economic Research and Modelling Infectious Diseases (CEV, CHERMID, Vaccine and Infectious Disease Institute, University of Antwerp) have collaborated over the past 15 years. This book demonstrates the past and current research activities of these institutes and can be considered to be a milestone in this collaboration. This book is focused on the application of modern statistical methods and models to estimate infectious disease parameters. We want to provide the readers with software guidance, such as R packages, and with data, as far as they can be made publicly available.

Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R - Order-Restricted Analysis of Microarray... Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R - Order-Restricted Analysis of Microarray Data (Paperback, 2012)
Danyu Lin, Ziv Shkedy, Daniel Yekutieli, Dhammika Amaratunga, Luc Bijnens
R933 Discovery Miles 9 330 Special order

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.

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