Strategies in Biomedical Data Science : Driving Force for Innovation.

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 demon...

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Bibliographic Details
Main Author: Etching, Jay
Format: eBook
Language:English
Published: Somerset : John Wiley & Sons, Incorporated, 2016.
Subjects:
Online Access:Click for online access

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245 1 0 |a Strategies in Biomedical Data Science :  |b Driving Force for Innovation. 
260 |a Somerset :  |b John Wiley & Sons, Incorporated,  |c 2016. 
300 |a 1 online resource (479 pages) 
336 |a text  |b txt  |2 rdacontent 
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505 0 |a Additional Praise; Wiley & SAS Business Series; Title page; Copyright; Foreword; Acknowledgments; Introduction; WHO SHOULD READ THIS BOOK?; WHAT'S IN THIS BOOK?; HOW TO CONTACT US; Chapter 1 Healthcare, History, and Heartbreak; TOP ISSUES IN HEALTHCARE; DATA MANAGEMENT; BIOSIMILARS, DRUG PRICING, AND PHARMACEUTICAL COMPOUNDING; PROMISING AREAS OF INNOVATION; CONCLUSION; NOTES; Chapter 2 Genome Sequencing; CHALLENGES OF GENOMIC ANALYSIS; THE LANGUAGE OF LIFE; A BRIEF HISTORY OF DNA SEQUENCING; DNA SEQUENCING AND THE HUMAN GENOME PROJECT; SELECT TOOLS FOR GENOMIC ANALYSIS; The R Project. 
505 8 |a Genome Analysis ToolkitMolecular Evolutionary Genetics Analysis; Bowtie; CONCLUSION; Notes; Note; Chapter 3 Data Management; BITS ABOUT DATA; DATA TYPES; DATA SECURITY AND COMPLIANCE; DATA STORAGE; SWIFTSTACK; CONCLUSION; NOTES; Note; Chapter 4 Designing a Data-Ready€Network Infrastructure; RESEARCH NETWORKS: A PRIMER; ESNET AT 30: EVOLVING TOWARD EXASCALE AND RAISING EXPECTATIONS; INTERNET2 INNOVATION PLATFORM; ADVANCES IN NETWORKING; INFINIBAND AND MICROSECOND LATENCY; THE FUTURE OF HIGH-PERFORMANCE FABRICS; NETWORK FUNCTION VIRTUALIZATION; SOFTWARE-DEFINED NETWORKING; OPENDAYLIGHT. 
505 8 |a CONCLUSIONNOTES; Chapter 5 Data-Intensive Compute Infrastructures; BIG DATA APPLICATIONS IN HEALTH INFORMATICS; SOURCES OF BIG DATA IN HEALTH INFORMATICS; INFRASTRUCTURE FOR BIG DATA ANALYTICS; FUNDAMENTAL SYSTEM PROPERTIES; GPU-ACCELERATED COMPUTING AND BIOMEDICAL INFORMATICS; CONCLUSION; NOTES; NOTES; INTRODUCTION; EVIS; SCIENTIFIC COMPUTING; VALIDATION; MEDICAL DEVICE DEVELOPMENT; CONCLUSION; Note; Chapter 6 Cloud Computing and Emerging Architectures; CLOUD BASICS; CHALLENGES FACING CLOUD COMPUTING APPLICATIONS IN BIOMEDICINE; HYBRID CAMPUS CLOUDS; RESEARCH AS A SERVICE. 
505 8 |a FEDERATED ACCESS WEB PORTALSCLUSTER HOMOGENEITY; EMERGING ARCHITECTURES (ZETA ARCHITECTURE); CONCLUSION; NOTES; Chapter 7 Data Science; NOSQL APPROACHES TO BIOMEDICAL DATA SCIENCE; USING SPLUNK FOR DATA ANALYTICS; STATISTICAL ANALYSIS OF GENOMIC DATA WITH HADOOP; EXTRACTING AND TRANSFORMING GENOMIC DATA; PROCESSING EQTL DATA; GENERATING MASTER SNP FILES FOR CASES AND CONTROLS; GENERATING GENE EXPRESSION FILES FOR CASES AND€CONTROLS; CLEANING RAW DATA USING MAPREDUCE; TRANSPOSE DATA USING PYTHON; STATISTICAL ANALYSIS USING SPARK; HIVE TABLES WITH PARTITIONS; CONCLUSION; NOTES. 
505 8 |a Appendix: A Brief Statistics Primer Content Contributed by Daniel Peñnaherrera, July 13, 2016FOUNDATIONS; POPULATION AND SAMPLE; RANDOM VARIABLES; EXPECTED VALUE AND VARIANCE; REGRESSION ANALYSIS; MULTIVARIATE LINEAR REGRESSION; LOGISTIC REGRESSION; Chapter 8 Next-Generation Cyberinfrastructures; Next-Generation Cyber Capability; NGCC DESIGN AND INFRASTRUCTURE; Conclusion; NOTE; Conclusion; Appendix A The Research Data Management Survey; Appendix B Central IT and Research Support; INSTITUTIONAL DEMOGRAPHICS (BACKGROUND); OVERVIEW OF CENTRAL IT ORGANIZATIONS; CENTRAL IT INFRASTRUCTURE. 
500 |a CENTRAL IT RESEARCH SUPPORT SERVICES. 
520 |a 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 entails -Explore the available advanced analytic resources and tools -Learn how bioinformatics as a service is quickly becoming reality -Examine the future of IOT and the deluge of personal device data The 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. 
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650 0 |a Medical informatics. 
650 0 |a Medicine  |x Data processing. 
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650 7 |a Biotechnology  |x Data processing  |2 fast 
650 7 |a Medical informatics  |2 fast 
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