Modeling dose response microarray data (13 résultats)
Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R : Order Restricted Analysis of Microarray Data
Lin, Dan (EDT); Shkedy, Ziv (EDT); Yekutieli, Daniel (EDT); Amaratunga, Dhammika (EDT); Bijnens, Luc (EDT)
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Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R : Order Restricted Analysis of Microarray Data
Lin, Dan (EDT); Shkedy, Ziv (EDT); Yekutieli, Daniel (EDT); Amaratunga, Dhammika (EDT); Bijnens, Luc (EDT)
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Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R : Order Restricted Analysis of Microarray Data
Lin, Dan (EDT); Shkedy, Ziv (EDT); Yekutieli, Daniel (EDT); Amaratunga, Dhammika (EDT); Bijnens, Luc (EDT)
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Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R : Order Restricted Analysis of Microarray Data
Lin, Dan (EDT); Shkedy, Ziv (EDT); Yekutieli, Daniel (EDT); Amaratunga, Dhammika (EDT); Bijnens, Luc (EDT)
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Vendeur : GreatBookPricesUK, Woodford Green, Royaume-UniGreatBookPricesUK
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Langue : anglais
Edité par Springer Verlag, 2012
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Paperback. Etat : Brand New. 2012 edition. 297 pages. 9.00x6.00x0.50 inches. In Stock.
Langue : anglais
Edité par Springer, Springer Vieweg, 2012
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Taschenbuch. Etat : 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. Etat : Neu. Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R | Order-Restricted Analysis of Microarray Data | Dan Lin (u. a.) | Taschenbuch | xv | Englisch | 2012 | Springer | EAN 9783642240065 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Hei…delberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Etat : Gut. Zustand: Gut | Seiten: 300 | Sprache: Englisch | Produktart: Bücher | 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 t…his 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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Langue : anglais
Edité par Springer Berlin Heidelberg Aug 2012, 2012
Série : Use R!, Livre 35 sur 68. Livre 35 sur 68 - Use R!
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Etat : 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.
Langue : anglais
Edité par Springer Berlin Heidelberg, 2012
Série : Use R!, Livre 35 sur 68. Livre 35 sur 68 - Use R!
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Etat : 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 estimati…on of normal means under o.
Langue : anglais
Edité par Springer, Springer Vieweg Aug 2012, 2012
Série : Use R!, Livre 35 sur 68. Livre 35 sur 68 - Use R!
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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 a…nalyze 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 KG, Sachsenplatz 4-6, 1201 Wien 300 pp. Englisch.
