A practical guide to turning complex microbial data into biological insight
Computational Techniques for Microbiologists: A Hands-On Approach provides a comprehensive introduction to data-driven analysis in microbiology, with a focus on the unique challenges of microbial datasets, including diverse organisms, incomplete genomes, and complex multi-species communities. As biological data production accelerates in both speed and scale, microbiologists increasingly need analytical skills to transform raw information into meaningful interpretation. This book meets that need with an accessible, example-based framework.
Readers are guided through the lifecycle of microbial data analysis and foundational concepts in bioinformatics, microbial data science, and statistics, using parallel approaches that span graphical tools, command-line methods, and scripting environments. This flexible structure allows readers with different technical backgrounds to engage at their own pace while developing computational literacy. The book follows end-to-end workflows, guiding readers from raw sequencing data through interpretation and biological insight.
Featuring real datasets, case studies, and practical exercises spanning clinical, environmental, and experimental microbiology, the book emphasizes reproducibility, transparency, and best practices aligned with current research and publishing standards. It also introduces approaches for integrating data across molecular layers, enabling a systems-level understanding of microbial biology.
Publicly available datasets, Jupyter notebooks, and workflows are available online to support hands-on learning and real-world application.
