Strategies in Biomedical Data Science

Driving Force for Innovation

Inbunden, Engelska, 2017

849 kr

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An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing deluge of healthcare data. Beginning with a look at our current top-down methodologies, this book demonstrates the ways in which both technological development and more effective use of current resources can better serve both patient and payer. The discussion explores the aggregation of disparate data sources, current analytics and toolsets, the growing necessity of smart bioinformatics, and more as data science and biomedical science grow increasingly intertwined. You'll dig into the unknown challenges that come along with every advance, and explore the ways in which healthcare data management and technology will inform medicine, politics, and research in the not-so-distant future. Real-world use cases and clear examples are featured throughout, and coverage of data sources, problems, and potential mitigations provides necessary insight for forward-looking healthcare professionals. Big Data has been a topic of discussion for some time, with much attention focused on problems and management issues surrounding truly staggering amounts of data. This book offers a lifeline through the tsunami of healthcare data, to help the medical community turn their data management problem into a solution. Consider the data challenges personalized medicine entailsExplore the available advanced analytic resources and toolsLearn how bioinformatics as a service is quickly becoming realityExamine the future of IOT and the deluge of personal device dataThe sheer amount of healthcare data being generated will only increase as both biomedical research and clinical practice trend toward individualized, patient-specific care. Strategies in Biomedical Data Science provides expert insight into the kind of robust data management that is becoming increasingly critical as healthcare evolves.

Produktinformation

Utgivningsdatum2017-03-07
Mått183 x 257 x 46 mm
Vikt885 g
FormatInbunden
SpråkEngelska
SerieWiley and SAS Business Series
Antal sidor464
FörlagJohn Wiley & Sons Inc
MedarbetareBuetow,Ken
ISBN9781119232193

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Foreword xiAcknowledgments xvIntroduction 1Who Should Read This Book? 3What’s in This Book? 4How to Contact Us 6Chapter 1 Healthcare, History, and Heartbreak 7Top Issues in Healthcare 9Data Management 16Biosimilars, Drug Pricing, and Pharmaceutical Compounding 18Promising Areas of Innovation 19Conclusion 25Notes 25Chapter 2 Genome Sequencing: Know Thyself, One Base Pair at a Time 27Content contributed by Sheetal Shetty and Jacob BrillChallenges of Genomic Analysis 29The Language of Life 30A Brief History of DNA Sequencing 31DNA Sequencing and the Human Genome Project 35Select Tools for Genomic Analysis 38Conclusion 47Notes 48Chapter 3 Data Management 53Content contributed by Joe ArnoldBits about Data 54Data Types 56Data Security and Compliance 59Data Storage 66SwiftStack 70OpenStack Swift Architecture 78Conclusion 94Notes 94Chapter 4 Designing a Data-Ready Network Infrastructure 105Research Networks: A Primer 108ESnet at 30: Evolving toward Exascale and Raising Expectations 109Internet2 Innovation Platform 111Advances in Networking 113InfiniBand and Microsecond Latency 114The Future of High-Performance Fabrics 117Network Function Virtualization 119Software-Defined Networking 121OpenDaylight 122Conclusion 157Notes 157Chapter 5 Data-Intensive Compute Infrastructures 163Content contributed by Dijiang Huang, Yuli Deng, Jay Etchings, Zhiyuan Ma, and Guangchun LuoBig Data Applications in Health Informatics 166Sources of Big Data in Health Informatics 168Infrastructure for Big Data Analytics 171Fundamental System Properties 186GPU-Accelerated Computing and Biomedical Informatics 187Conclusion 190Notes 191Chapter 6 Cloud Computing and Emerging Architectures 211Cloud Basics 213Challenges Facing Cloud Computing Applications in Biomedicine 215Hybrid Campus Clouds 216Research as a Service 217Federated Access Web Portals 219Cluster Homogeneity 220Emerging Architectures (Zeta Architecture) 221Conclusion 229Notes 229Chapter 7 Data Science 235NoSQL Approaches to Biomedical Data Science 237Using Splunk for Data Analytics 244Statistical Analysis of Genomic Data with Hadoop 250Extracting and Transforming Genomic Data 253Processing eQTL Data 256Generating Master SNP Files for Cases and Controls 259Generating Gene Expression Files for Cases and Controls 260Cleaning Raw Data Using MapReduce 261Transpose Data Using Python 263Statistical Analysis Using Spark 264Hive Tables with Partitions 268Conclusion 270Notes 270Appendix: A Brief Statistics Primer 290Content Contributed by Daniel PeñaherreraChapter 8 Next-Generation Cyberinfrastructures 307Next-Generation Cyber Capability 308NGCC Design and Infrastructure 310Conclusion 327Note 330Conclusion 335Appendix A The Research Data Management Survey: From Concepts to Practice 337Brandon Mikkelsen and Jay EtchingsAppendix B Central IT and Research Support 353Gregory D. PalmerAppendix C HPC Working Example: Using Parallelization Programs Such as GNU Parallel and OpenMP with Serial Tools 377Appendix D HPC and Hadoop: Bridging HPC to Hadoop 385Appendix E Bioinformatics + Docker: Simplifying Bioinformatics Tools Delivery with Docker Containers 391Glossary 399About the Author 419About the Contributors 421Index 427