Big data analysis for bioinformatics and biomedical discoveries
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- 9781498724524
- 570.285 YE-B
Item type | Current library | Collection | Call number | Status | Date due | Barcode | Item holds |
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IIITD General Stacks | Biology | 570.285 YE-B (Browse shelf(Opens below)) | Available | 009277 | ||
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IIITD Reference | Biology | REF 570.285 YE-B (Browse shelf(Opens below)) | Not for loan | 008218 |
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REF 570.285 JON-I Introduction to bioinformatics algorithms | REF 570.285 LOW-B Bioinformatics : | REF 570.285 SIN-F Fundamentals of bioinformatics and computational Biology : | REF 570.285 YE-B Big data analysis for bioinformatics and biomedical discoveries | REF 571.4 BIA-B Biophysics : | REF 571.4 JUE-F Fundamental concepts in biophysics | REF 571.4 NEL-B Biological physics : |
"A Chapman & Hall book."
Includes bibliographical references and index.
"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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