Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Statistics for Biology and Health)

Bioconductor is a widely adopted open-source software project designed for the analysis and interpretation of high-throughput data in genomics and molecular biology. Built on the R statistical programming environment, Bioconductor provides a powerful framework for researchers working with large-scale biological datasets.

This comprehensive volume covers the essential components of the Bioconductor ecosystem, spanning a wide range of tools and techniques, including:

• Data import and preprocessing for high-throughput platforms such as microarrays, proteomics, and flow cytometry

• Curation and integration of biological metadata to support statistical modeling and biological interpretation

• Advanced statistical analysis, including visualization tools and machine learning methods tailored for genomic data

• Modeling and visualizing complex biological networks and graphs

Authored collaboratively by many of Bioconductor’s core developers—who are also prominent academic researchers—each chapter is supported by real, publicly available datasets. A significant portion of the book is dedicated to fully developed case studies, demonstrating practical applications of the tools in real-world research contexts.

More than just a static reference, this book is an interactive resource. All code used to generate the results, figures, and tables is available on a companion website, enabling readers to reproduce every analysis and explore the data hands-on.