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Richly illustrated in color, Statistics and Data Analysis for Microarrays Using R and Bioconductor, Second Edition provides a clear and;
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describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting;
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describes wet-bench technologies that produce the data for analysis and explains how to preprocess the data to remove systematic artifacts resulting;
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-quality figures using the power of RBioconductor and ggplot2. This book will teach you 'cooking from scratch', from raw data to beautiful;
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well as standard data normalization and analysis techniques. Statistics for Microarrays: Design, Analysis and Inference is the first book that;
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Statistics and Data Visualization Using R: The Art and Practice of Data Analysis teaches students statistics visually, focusing on;
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Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments. Its;
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Over 60 recipes to model and handle real-life biological data using modern libraries from the R ecosystem Key Features Apply modern R;
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also in computer science and the tools and techniques of data analysis.To help meet the challenges of DNA research, Data Analysis Tools for DNA;
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filtering, primary pattern analysis, and machine learning algorithms using R and Python are demonstrated for gene-expression microarrays, genotyping;
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the freeware R - a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the;
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Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and;
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Full four-color book. Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R;
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growing use of DNA microarray data in the diagnosis of and treatment planning for a large number of human cancers.* Uniquely deals with direct;
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applied problems, for which step-by-step instructions for using R and R-Commander are provided. Topics include data exploration, estimation;
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readers to develop computational skills and problem-solving competence using the open source language, R. Mustapha Abiodun Akinkunmi uses;
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Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners;
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Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners;
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with R and using it for simple summary statistics, hypothesis testing, and graphs * Shows how to use R for formula notation, complex statistics;
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;
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R is the most widely used open-source statistical and programming environment for the analysis and visualization of biological data;
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, behavioral, and natural sciences, Univariate, Bivariate, and Multivariate Statistics Using R offers an easy-to-use guide for performing data analysis;
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After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured;
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After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured;
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Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist;
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Using IBM (R) SPSS (R) Statistics for Research Methods and Social Science Statistics is the perfect companion for students who are learning;
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. Statistics and Probability with Applications for Engineers and Scientists using MINITAB, R and JMP, Second Edition is broken into two parts. Part I;
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