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Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R

Name: Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R
Brand: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
SKU: 9783642240065
Price: 277.38 RON
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Order-Restricted Analysis of Microarray Data

Autor: Dan Lin, Ziv Shkedy, Daniel Yekutieli

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Legare: Carte broșată

Editura: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

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This book focuses on the analysis of dose-response microarray data in pharmaceutical setting, the go...

Informații despre carte

Autor

Dan Lin, Ziv Shkedy, Daniel Yekutieli

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2012

Pagini

282

EAN

9783642240065

ISBN

3642240062

Enbook ID

01658842

Editura

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Greutate

460

Dimensiuni

157 x 236 x 16

Descriere completă

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.