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Computational Genomics with R
Computational Genomics with R
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Computational Genomics with R is a book that provides a comprehensive introduction to genomic data analysis using the R programming language. It covers topics from R programming, machine learning, and statistics to the latest techniques in genomic data analysis, with practical and well-documented examples in R. The book is designed for beginners and advanced practitioners in the field of computational genomics, with different starting points depending on the reader's background.
Format: Hardback
Length: 440 pages
Publication date: 10 December 2020
Publisher: Taylor & Francis Inc
Computational Genomics with R is a comprehensive guide for beginners and advanced practitioners in genomic data analysis. It covers a wide range of topics, including R programming, machine learning, statistics, and the latest techniques in genomic data analysis. The book provides accessible information and explanations, with a strong focus on the genomics context. It offers practical and well-documented examples in R, allowing readers to analyze their data with ease.
As computational genomics is an interdisciplinary field, the book caters to individuals with different backgrounds. Biologists, for instance, can skip sections on basic genome biology and start with R programming, while computer scientists can begin with genome biology.
After completing this book, readers will have a solid foundation in R and be able to apply it to specialized uses in computational genomics. They will be familiar with statistics, supervised and unsupervised learning techniques, data modeling, exploratory analysis of high-dimensional data, genomic intervals, operations, processing, quality checking, sequence analysis, visualization techniques, and the analysis of different high-throughput sequencing data.
The book is organized into chapters, each covering a specific topic. The first chapter provides an introduction to R and computational genomics, while subsequent chapters delve into more advanced topics such as machine learning, statistical analysis, and genomic data visualization. Each chapter includes exercises and examples to reinforce the learning process.
In conclusion, Computational Genomics with R is an essential resource for anyone interested in genomic data analysis. It provides a comprehensive and up-to-date introduction to the field, covering a wide range of topics and offering practical guidance through examples and exercises. Whether you are a beginner or an experienced practitioner, this book will help you unlock the power of R and advance your understanding of computational genomics.
Weight: 1132g
Dimension: 184 x 261 x 31 (mm)
ISBN-13: 9781498781855
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