Modeling Dose Response Microarray Data (15 results)

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Taschenbuch. Condition: Neu. Neuware -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 rateAll methodological issues in the book are illustrated using real-world examples of dose-response microarray datasets from early drug development experiments.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 300 pp. Englisch.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 rateAll 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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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 rateAll methodological issues in the book are illustrated using real-world examples of dose-response microarray datasets from early drug development experiments. 300 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book focuses on the analysis of microarray data in the dose-response setting in early drug development experiments in the pharmaceutical industry Part I discusses the dose-response setting and the problem of estimation of normal means under o.