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Introduction to Computational Metagenomics

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English | 2022 | ISBN: 9811242461 | 210 pages | True PDF EPUB | 37.02 MB
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:
PrefaceAcknowledgmentsComputational Metagenomics: A Metagenomics PerspectiveComputational Metagenomics: A Data Engineering PerspectiveComputational Metagenomics: An Algorithmic PerspectiveHardware and Software Aspects for Scalable AnalysisMetagenomics Data Quality ImprovementExploring Community Diversity: Taxonomical AnalysesFunctional Metagenomics: Gene and Pathway-Based AnalysesDeconvolute Community Metagenome into Single GenomesSingle Cell MetagenomicsInteractions Between Microbes and Their EnvironmentBibliographyIndex
Readership: Graduate students and advanced undergraduates from genomics science or computer science fields, beginner researchers from similar disciplines.


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