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Leading biostatisticians and biomedical researchers describe many of the key techniques used to solve commonly occurring data analytic problems in molecular biology, and demonstrate how these methods can be used in the development of new markers for exposure to a risk factor or for disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, genetic susceptibility and association, evaluation of new biomarkers, and power analysis and sample size.
The book presents the reader with a representative sampling of biostatistical applications that are used in the study of molecular biology with an emphasis on the development of biomarkers for clinical applications. - Biotech Software & Internet Report In 10 chapters the authors fulfill the aim to provide sufficient information to cover area of both biostatistics and molecular biology...authors pay attention to give accurate explanation of basic biological and statistical terms. This is worthwhile for statisticians who want to work in molecular biology and for molecular biologists to be in touch with recent advances in comprehensive high-throughput laboratory methods. - Neoplasma
Statistical Contributions to Molecular Biology. Linking Image Quantitation and Data Analysis. Introduction to Microarray Experimentation and Analysis. Statistical Methods for Proteomics. Statistical Methods for Assessing Biomarkers. Power and Sample Size Considerations in Molecular Biology. Models for Determining Genetic Susceptibility and Predicting Outcome. Multiple Tests for Genetic Effects in Association Studies. Statistical Considerations in Assessing Molecular Markers for Cancer Prognosis and Treatment Efficacy. Power of the Rank Test for Multi-Strata Case-Control Studies with Ordinal Exposure Variables. Index.
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