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

for early drug development experiments and to provide user-friendly R packages that can be used to analyze this data. It is intended for;

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Dose-Response Analysis Using R

numerous real data examples to illustrate the methodology. R code is integrated into the text to give guidance on applying the methods;

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Dose-Response Analysis Using R

this development. Key Features: Provides a practical and comprehensive overview of dose-response analysis. Includes numerous real data examples;

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Exposure-Response Modeling

extensive practical experience in drug development, Exposure-Response Modeling: Methods and Practical Implementation explores a wide range of topics;

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Exposure-Response Modeling

extensive practical experience in drug development, Exposure-Response Modeling: Methods and Practical Implementation explores a wide range of topics;

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Genomics in Drug Discovery and Development

microarray data analysis, Genomics in Drug Discovery and Development introduces readers to the biomarker, pharmacogenomic, and toxicogenomics toolbox;

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Dose Finding in Drug Development

is a summary of results obtained from many scientific experiments. The book introduces the drug development process, the design and the;

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A Practical Approach to Microarray Data Analysis

In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry;

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Drug Synergism and Dose-Effect Data Analysis

conceptual background, the algorithms, and new research developments. In short, Drug Synergism and Dose-Effect Data Analysis has everything you need;

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Drug Synergism and Dose-Effect Data Analysis

conceptual background, the algorithms, and new research developments. In short, Drug Synergism and Dose-Effect Data Analysis has everything you need;

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Using R for Item Response Theory Model Applications

, medical research, and business as well. Using R for Item Response Theory Model Applications is a practical guide for students, instructors;

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Using R for Item Response Theory Model Applications

, medical research, and business as well. Using R for Item Response Theory Model Applications is a practical guide for students, instructors;

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Categorical Data Analysis and Multilevel Modeling Using R

Categorical Data Analysis and Multilevel Modeling Using R provides a practical guide to regression techniques for analyzing binary, ordinal;

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Uncertainty Modeling in Dose Response

exist in the various approaches to bench test problems. This book works with four bench test problems that were taken from real bioassay data;

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Analysis of Microarray Data: A Network-Based Approach

Functional Modules Using Microarray and Protein Interaction Data* Integrating Results from Literature Mining and Microarray Experiments to Infer Gene;

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Statistical Methods for Dose-Finding Experiments

Dose-finding experiments define the safe dosage of a drug in development, in terms of the quantity given to a patient. Statistical methods;

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Statistical Methods in Biomarker and Early Clinical Development

This contributed volume offers a much-needed overview of the statistical methods in early clinical drug and biomarker development. Chapters;

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Biomarker Analysis in Clinical Trials with R

Early Clinical Development, Pfizer, Inc. Biomarker Analysis in Clinical Trials with R offers practical guidance to statisticians in the;

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Biomarker Analysis in Clinical Trials with R

Early Clinical Development, Pfizer, Inc. Biomarker Analysis in Clinical Trials with R offers practical guidance to statisticians in the;

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Statistical Methods in Drug Combination Studies

The growing interest in using combination drugs to treat various complex diseases has spawned the development of many novel statistical;

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Statistics For Microarrays

, image analysis, normalization, quality control, and statistical inference. Features many examples throughout using real data from microarray;

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Modeling and Control of Infectious Diseases in the Host

presenting topics on quantitative decision-making that influence the development of drugs. The book presents modeling advances in different viral;

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Statistical Methods in Drug Combination Studies

The growing interest in using combination drugs to treat various complex diseases has spawned the development of many novel statistical;

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Fabrication of interpenetrating polymer network hydrogel microspheres

using response surface methodology corroborates that a two-factor central composite design is quite efficient in optimizing drug delivery;

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DNA Microarray Technology and Data Analysis in Cancer Research

DNA microarray technology has become a useful technique in gene expression analysis for the development of new diagnostic tools and for the;

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Methods of Microarray Data Analysis II

. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis II is the;

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Batch Effects and Noise in Microarray Experiments

in microarray data.* An extensive overview of current standardization initiatives.* All datasets and methods used in the chapters, as well as colour;

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