Nu se pretează? Nu contează! La noi puteți returna bunurile în 30 de zile
Cu un voucher cadou nu veți da greș. În schimbul voucherului, destinatarul își poate alege orice din oferta noastră.
30 de zile pentru retur bunuri
This book focuses on the analysis of dose-response microarray data in pharmaceutical setting, the goal being to cover this important topic for early drug development and to provide user-friendly R packages that can be used to analyze dose-response microarray 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 the likelihood ratio test and non-linear parametric models, which are used in the second part of the book. §Part II is the core of the book. Methodological topics discussed include:§· Multiplicity adjustment§· Test statistics and testing procedures for the analysis of dose-response microarray data§· Resampling-based inference and use of the SAM method at the presence of 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§· Hierarchical Bayesian models and non-linear models for dose-response microarray data§· Multiple contrast tests§All methodological issues in the book are illustrated using four real-world examples of dose-response microarray datasets from early drug development experiments.This book focuses on the analysis of dose-response microarray data in pharmaceutical setting, the goal being to cover this important topic for early drug development and to provide user-friendly R packages that can be used to analyze dose-response microarray 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 the likelihood ratio test and non-linear parametric models, which are used in the second part of the book. §Part II is the core of the book. Methodological topics discussed include:§· Multiplicity adjustment§· Test statistics and testing procedures for the analysis of dose-response microarray data §· Resampling-based inference and use of the SAM method at the presence of 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§· Hierarchical Bayesian models and non-linear models for dose-response microarray data§· Multiple contrast tests§All methodological issues in the book are illustrated using four real-world examples of dose-response microarray datasets from early drug development experiments.