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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 Hardback or Cased Book
ISBN-10 1498724523
ISBN-13 9781498724524
Publisher Taylor & Francis Inc
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Dec 22nd, 2015
Print length 294 Pages
Weight 586 grams
Dimensions 16.20 x 24.10 x 2.10 cms
Ksh 23,400.00
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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 enhances readers’ computational and quantitative skills so that they can exploit the Big Data being generated in the current omics era.

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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