Breakthroughs in high-throughput genome sequencing and high-performance computing technologies have enabled scientists to decode many genomes including our own. Now there is a bigger ambition: to get a holistic view of microbial communities within us and around us, gaining insights that could revolutionize the view about our health and our environment. In metagenomics, the DNAs of a microbial community are sequenced directly from the habitats without lab cultivation. This creates an enormous data challenge, as metagenomics projects can generate tens of tera bases of sequences, equivalent to tens of thousands of human genomes.This interdisciplinary book is essential reading for those who are interested in beginning their own journey in metagenomics data science. It is a prism to look through various intricate computational metagenomics problems and understand their three distinctive aspects: metagenomics, data engineering, and algorithms. It is specially tailored for graduate students and advanced undergraduates from genomics science or computer science fields, but beginner researchers from similar disciplines may also find it very useful.Key Features? It is the first book that systematically dissects key computational metagenomics problems in their metagenomics, computer science, and data science aspects? Unlike many other books in this field, this book manages to avoid jargons as much as possible without overly simplifying the essential concepts? This book focuses on practical knowledge rather than software tools. Tools can get obsolete quickly, but the knowledge will not? At the end of each chapter, there is a section that offers unique perspectives about what is coming in the near future. Thus, the book may stay relevant for a longer time
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