Breakthroughs in high-throughput genome sequencing and high-performance computing technologies have empowered scientists to decode many genomes including our own. Now they have a bigger ambition: to fully understand the vast diversity of microbial communities within us and around us, and to exploit their potential for the improvement of our health and environment. In this new field called metagenomics, microbial genomes are sequenced directly from the habitats without lab cultivation. Computational metagenomics, however, faces both a data challenge that deals with tens of tera-bases of sequences and an algorithmic one that deals with the complexity of thousands of species and their interactions.

This interdisciplinary book is essential reading for those who are interested in beginning their own journey in computational metagenomics. It is a prism to look through various intricate computational metagenomics problems and unravel their three distinctive aspects: metagenomics, data engineering, and algorithms. Graduate students and advanced undergraduates from genomics science or computer science fields will find that the concepts explained in this book can serve as stepping stones for more advanced topics, while metagenomics practitioners and researchers from similar disciplines may use it to broaden their knowledge or identify new research targets.

Contents:

• Preface


• Acknowledgments


• Computational Metagenomics: A Metagenomics Perspective


• Computational Metagenomics: A Data Engineering Perspective


• Computational Metagenomics: An Algorithmic Perspective


• Hardware and Software Aspects for Scalable Analysis


• Metagenomics Data Quality Improvement


• Exploring Community Diversity: Taxonomical Analyses


• Functional Metagenomics: Gene and Pathway-Based Analyses


• Deconvolute Community Metagenome into Single Genomes


• Single Cell Metagenomics


• Interactions Between Microbes and Their Environment


• Bibliography


• Index

Readership: Graduate students and advanced undergraduates from genomics science or computer science fields, beginner researchers from similar disciplines.

'This book combines the fundamental knowledge of data science and microbiology. It clearly shows the research goals and obstacles of microbiomics, and accurately introduces the practical knowledge and tools of computational science. This book is the perfect 'primer' for beginners in metagenomics. It is friendly for computer science background readers. You can understand and gain a lot from it even with minimal prior biologic knowledge.' - Li DengAssociate ProfessorShanghai University

'Computational metagenomics is an interdisciplinary field that aims to develop novel algorithms and bioinformatic tools to explore large volumes of metagenome data, helping to mine, understand, and interpret the intricate connections between human societies and microbial communities. This book contains the core knowledge required for this field. Readers from schools or companies will find this book very useful in their studies and work, as the writer of this book is an expert with extensive mentoring experience in this field. I congratulate the author for sharing his insights to contribute to the community.' - Lizhen Shi Florida Polytechnic University

'It's an excellent book for a wide audience of researchers, especially for people who have less program background. The three pillars of computational metagenomics points the way to a clearly understanding of current state as well as the future development of this subject.' - Yinyue DuPhD student, University of California, Merced

'As someone who has spent the last decade performing leading edge microbiome and metagenomics research I was astounded that a book titled 'Introduction to ...' was able to teach me so much.' See full review - Andrew BrooksPostdoctoral Researchers and NIH Fellowship Recipient, Michael Snyder LabStanford Medicine Department of Genetics