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Provides a sample of applications of biostatistics to commonly occurring analytical problems in molecular biology. The ten papers are arranged in the order in which the methods of analysis would be utilized in developing a new marker for exposure to a risk factor or for a disease outcome. The contributors describe microarray analysis and proteomics, discuss power and sample size considerations, and present models for determining genetic susceptibility and predicting outcome. Statistical issues related to the assessment of molecular markers for cancer prognosis and treatment efficacy are also covered.Book News, Inc.

Book Info

Univ. of Louisville, KY. Applies biostatistics to the study of genetics and the causes and treatment of disease. Covers recent developments in image quantitation, microarrays, and proteomics. Discusses the use of data management software. Includes numerous data sets and software recommendations

Dedication
Preface
Contributors
1 Statistical Contributions to Molecular Biology 1
2 Linking Image Quantitation and Data Analysis 15
3 Introduction to Microarray Experimentation and Analysis 29
4 Statistical Methods for Proteomics 51
5 Statistical Methods for Assessing Biomarkers 81
6 Power and Sample Size Considerations in Molecular Biology 111
7 Models for Determining Genetic Susceptibility and Predicting Outcome 131
8 Multiple Tests for Genetic Effects in Association Studies 143
9 Statistical Considerations in Assessing Molecular Markers for Cancer Prognosis and Treatment Efficacy 169
10 Power of the Rank Test for Multi-Strata Case-Control Studies with Ordinal Exposure Variables 191
Index 203