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Big Data Analysis for Bioinformatics and Biomedical Discoveries
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Big Data Analysis for Bioinformatics and Biomedical Discoveries

Book Details

Format Paperback / Softback
ISBN-10 0367783274
ISBN-13 9780367783273
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Mar 31st, 2021
Print length 274 Pages
Weight 446 grams
Dimensions 15.50 x 23.30 x 2.60 cms
Product Classification: Biology, life sciences
Ksh 9,000.00
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This book is a practical guide to the nuts and bolts of Big Data, enabling readers to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries, carry out translational medical research, and implement personalized genomic medicine. Contributing to the NIH Big Data to Knowledge (BD2K) initiative, the book

Demystifies Biomedical and Biological Big Data Analyses



Big Data Analysis for Bioinformatics and Biomedical Discoveries provides a practical guide to the nuts and bolts of Big Data, enabling you to quickly and effectively harness the power of Big Data to make groundbreaking biological discoveries, carry out translational medical research, and implement personalized genomic medicine. Contributing to the NIH Big Data to Knowledge (BD2K) initiative, the book enhances your computational and quantitative skills so that you can exploit the Big Data being generated in the current omics era.





The book explores many significant topics of Big Data analyses in an easily understandable format. It describes popular tools and software for Big Data analyses and explains next-generation DNA sequencing data analyses. It also discusses comprehensive Big Data analyses of several major areas, including the integration of omics data, pharmacogenomics, electronic health record data, and drug discovery.





Accessible to biologists, biomedical scientists, bioinformaticians, and computer data analysts, the book keeps complex mathematical deductions and jargon to a minimum. Each chapter includes a theoretical introduction, example applications, data analysis principles, step-by-step tutorials, and authoritative references.


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