Introduction to computational metagenomics

By:

Wang, Zhong

Material type: Text

9789811242465

Subject(s):

DDC classification:

572.8 WAN-I

LOC classification:

QH447 .W365 2022

NLM classification:

QU 26.5

Contents:

1. Computational metagenomics : a metagenomics perspective 2. Computational metagenomics : a data engineering perspective 3. Computational metagenomics : an algorithmic perspective 4. Hardware and software aspects for scalable analysis 5. Metagenomics data quality improvement 6. Exploring community diversity : taxonomic analyses 7. Functional metagenomics : gene and pathway-based analyses 8. Deconvolute community metagenome into single genomes 9. Single cell metagenomics 10. Interactions between microbes and their environment.

Summary: "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"--

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Holdings
Item type	Current library	Collection	Call number	Status	Notes	Barcode	Course reserves
Books	IIITD Reference	Biology	CB 572.8 WAN-I (Browse shelf(Opens below))	Available	DBT Project Grant	012691
Books	IIITD Reference	Biology	CB 572.8 WAN-I (Browse shelf(Opens below))	Available	DBT Project Grant	012692
Books	IIITD Reference	Biology	REF 572.8 WAN-I (Browse shelf(Opens below))	Not for loan		011372	Computational Metagenomics UG/PG MNS Human Microbiome Data Science (New) UG/PG (REST) WNT24

Total holds: 0

Includes bibliographical references (pages 173-187) and index.

"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"--

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