{"product_id":"9783642240065","title":"Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R","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\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003ePublication Year: \u003c\/strong\u003e2012\u003cbr\u003e\u003cstrong\u003eImprint: \u003c\/strong\u003eSpringer Berlin Heidelberg\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003eFormat: P\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003eWeight (Gram): 462\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003cbr\u003e\u003cstrong\u003e\u003c\/strong\u003e\u003c\/p\u003e","brand":"Dan Lin","offers":[{"title":"Default Title","offer_id":41263679963314,"sku":"9783642240065","price":1261617.96,"currency_code":"IDR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0502\/5382\/4178\/products\/3642240062.01_SCLZZZZZZZ.jpg?v=1635984863","url":"https:\/\/readabook.store\/en-id\/products\/9783642240065","provider":"READABOOK BY ALKEM","version":"1.0","type":"link"}