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R Bioinformatics Cookbook

You're reading from   R Bioinformatics Cookbook Utilize R packages for bioinformatics, genomics, data science, and machine learning

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781837634279
Length 396 pages
Edition 2nd Edition
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Author (1):
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Dan MacLean Dan MacLean
Author Profile Icon Dan MacLean
Dan MacLean
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Toc

Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Setting Up Your R Bioinformatics Working Environment 2. Chapter 2: Loading, Tidying, and Cleaning Data in the tidyverse FREE CHAPTER 3. Chapter 3: ggplot2 and Extensions for Publication Quality Plots 4. Chapter 4: Using Quarto to Make Data-Rich Reports, Presentations, and Websites 5. Chapter 5: Easily Performing Statistical Tests Using Linear Models 6. Chapter 6: Performing Quantitative RNA-seq 7. Chapter 7: Finding Genetic Variants with HTS Data 8. Chapter 8: Searching Gene and Protein Sequences for Domains and Motifs 9. Chapter 9: Phylogenetic Analysis and Visualization 10. Chapter 10: Analyzing Gene Annotations 11. Chapter 11: Machine Learning with mlr3 12. Chapter 12: Functional Programming with purrr and base R 13. Chapter 13: Turbo-Charging Development in R with ChatGPT 14. Index 15. Other Books You May Enjoy

Finding enriched KEGG pathways

Kyoto Encyclopedia of Genes and Genomes (KEGG) is a bioinformatics resource that integrates genomic, chemical, and systemic functional information. KEGG contains a comprehensive database of molecular networks that represent various biological systems, such as metabolic pathways, regulatory pathways, and signaling pathways.

KEGG is widely used in bioinformatics analysis to understand the relationships between genes, proteins, and other biomolecules in biological systems. It provides a wealth of information on the molecular mechanisms of various biological processes, such as metabolism, signal transduction, and disease pathways. Researchers can use KEGG to analyze their own datasets, such as gene expression data or protein-protein interaction data, and identify the key pathways that are affected by their experiments.

In this recipe, we’ll look at how to examine a gene list derived from experiments in order to find pathways using the free-to...

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