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<p>About this book <br>Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R.<br><br>This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including importation and preprocessing of high-throughput data from microarray, proteomic, and flow cytometry platforms:<br><br>Curation and delivery of biological metadata for use in statistical modeling and interpretation<br><br>Statistical analysis of high-throughput data, including machine learning and visualization<br><br>Modeling and visualization of graphs and networks<br><br>The developers of the software, who are in many cases leading academic researchers, jointly authored chapters. All methods are illustrated with publicly available data, and a major section of the book is devoted to exposition of fully worked case studies.<br><br>This book is more than a static collection of descriptive text, figures, and code examples that were run by the authors to produce the text; it is a dynamic document. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.<br><br>Written for: <br>Researchers, students<br></p>


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