{"product_id":"modeling-dose-response-microarray-data-in-dan-lin-9783642240065","title":"Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R: Order-Restricted Analysis of Microarray Data","description":"\u003cp\u003eThis 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.\u003c\/p\u003e\u003cp\u003ePart 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.\u003c\/p\u003e\u003cp\u003ePart II is the core of the book, in which we focus on the analysis of dose-response microarray data. Methodological topics discussed include: \u003c\/p\u003e\u003cp\u003e- Multiplicity adjustment\u003c\/p\u003e\u003cp\u003e- Test statistics and procedures for the analysis of dose-response microarray data\u003c\/p\u003e\u003cp\u003e- Resampling-based inference and use of the SAM method for small-variance genes in the data\u003c\/p\u003e\u003cp\u003e- Identification and classification of dose-response curve shapes\u003c\/p\u003e\u003cp\u003e- Clustering of order-restricted (but not necessarily monotone) dose-response profiles\u003c\/p\u003e\u003cp\u003e- Gene set analysis to facilitate the interpretation of microarray results\u003c\/p\u003e\u003cp\u003e- Hierarchical Bayesian models and Bayesian variable selection\u003c\/p\u003e\u003cp\u003e- Non-linear models for dose-response microarray data\u003c\/p\u003e\u003cp\u003e- Multiple contrast tests\u003c\/p\u003e\u003cp\u003e- Multiple confidence intervals for selected parameters adjusted for the false coverage-statement rate\u003c\/p\u003e\u003cp\u003eAll methodological issues in the book are illustrated using real-world examples of dose-response microarray datasets from early drug development experiments.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Dan Lin\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 3642240062\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9783642240065\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Springer\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 08\/26\/2012\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 282\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.93lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.18h x 6.12w x 0.60d\u003c\/p\u003e","brand":"Dan Lin","offers":[{"title":"Paperback","offer_id":48996313792767,"sku":"9783642240065","price":54.99,"currency_code":"USD","in_stock":true}],"url":"https:\/\/www.whiterainbookhouse.com\/products\/modeling-dose-response-microarray-data-in-dan-lin-9783642240065","provider":"WR Book House","version":"1.0","type":"link"}