Computational Genomics provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers approximately all topics, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples so readers can analyse their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology whereas a computer scientist might want to start with genome biology. This book’s main target audience are students of computational genomics to get a first look at the diversity of machine learning methods. The book will also serve well biomedical researchers needing a guide to packages that can help them with the analysis of data that they encounter in their work.