Optimal High-Throughput Screening

Practical Experimental Design and Data Analysis for Genome-Scale RNAi Research

Häftad, Engelska, 2011

408 kr

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Beskrivning

This concise, self-contained and cohesive book focuses on commonly used and recently developed methods for designing and analyzing high-throughput screening (HTS) experiments from a statistically sound basis. Combining ideas from biology, computing and statistics, the author explains experimental designs and analytic methods that are amenable to rigorous analysis and interpretation of RNAi HTS experiments. The opening chapters are carefully presented to be accessible both to biologists with training only in basic statistics and to computational scientists and statisticians with basic biological knowledge. Biologists will see how new experiment designs and rudimentary data-handling strategies for RNAi HTS experiments can improve their results, whereas analysts will learn how to apply recently developed statistical methods to interpret HTS experiments.

Produktinformation

Utgivningsdatum:2011-02-21
Mått:177 x 254 x 13 mm
Vikt:430 g
Format:Häftad
Språk:Engelska
Antal sidor:224
Förlag:Cambridge University Press
ISBN:9780521734448

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Mer om författaren

Dr Xiaohua Douglas Zhang is an associate director at Merck Research Laboratories. He has worked on data analysis for genome-wide RNAi research and microarrays in drug discovery and development for various diseases for many years. He has continuously developed novel analytic methods and experimental designs for quality control and hit selection in genome-scale RNAi research. He and his colleagues have published many papers in various peer-reviewed journals, including Cell Host and Microbe, Nucleic Acids Research, Bioinformatics, Genetic Epidemiology, the Journal of Biological Chemistry, Pharmacogenomics, Genomics and the Journal of Biomolecular Screening, among many others.

Innehållsförteckning

Part I. RNAi HTS and Data Analysis: 1. Introduction to genome-scale RNAi research; 2. Experimental designs; 3. Data display and normalization; 4. Quality control in genome-scale RNAi screens; 5. Hit selection in genome-scale RNAi screens without replicates; 6. Hit selection in genome-scale RNAi screens with replicates; Part II. Methodological Development for Analyzing RNAi HTS Screens: 7. Statistical methods for group comparison; 8. Statistical methods for assessing the size of siRNA effects.