Foreword |
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xi | |
Acknowledgments |
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xv | |
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1 | (2) |
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Who Should Read This Book? |
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3 | (1) |
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4 | (2) |
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6 | (1) |
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Chapter 1 Healthcare, History, and Heartbreak |
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7 | (20) |
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9 | (7) |
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16 | (2) |
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Biosimilars, Drug Pricing, and Pharmaceutical Compounding |
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18 | (1) |
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Promising Areas of Innovation |
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19 | (6) |
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25 | (1) |
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25 | (2) |
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Chapter 2 Genome Sequencing: Know Thyself, One Base Pair at a Time |
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27 | (26) |
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Challenges of Genomic Analysis |
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29 | (1) |
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30 | (1) |
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A Brief History of DNA Sequencing |
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31 | (4) |
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DNA Sequencing and the Human Genome Project |
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35 | (3) |
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Select Tools for Genomic Analysis |
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38 | (9) |
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47 | (1) |
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48 | (5) |
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Chapter 3 Data Management |
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53 | (52) |
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54 | (2) |
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56 | (3) |
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Data Security and Compliance |
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59 | (7) |
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66 | (4) |
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70 | (8) |
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OpenStack Swift Architecture |
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78 | (16) |
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94 | (1) |
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94 | (11) |
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Chapter 4 Designing a Data-Ready Network Infrastructure |
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105 | (58) |
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Research Networks: A Primer |
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108 | (1) |
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ESnet at 30: Evolving toward Exascale and Raising Expectations |
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109 | (2) |
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Internet2 Innovation Platform |
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111 | (2) |
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113 | (1) |
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InfiniBand and Microsecond Latency |
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114 | (3) |
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The Future of High-Performance Fabrics |
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117 | (2) |
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Network Function Virtualization |
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119 | (2) |
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Software-Defined Networking |
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121 | (1) |
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122 | (35) |
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157 | (1) |
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157 | (6) |
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Chapter 5 Data-Intensive Compute Infrastructures |
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163 | (48) |
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Big Data Applications in Health Informatics |
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166 | (2) |
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Sources of Big Data in Health Informatics |
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168 | (3) |
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Infrastructure for Big Data Analytics |
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171 | (15) |
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Fundamental System Properties |
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186 | (1) |
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GPU-Accelerated Computing and Biomedical Informatics |
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187 | (3) |
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190 | (1) |
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191 | (20) |
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Chapter 6 Cloud Computing and Emerging Architectures |
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211 | (24) |
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213 | (2) |
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Challenges Facing Cloud Computing Applications in Biomedicine |
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215 | (1) |
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216 | (1) |
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217 | (2) |
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Federated Access Web Portals |
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219 | (1) |
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220 | (1) |
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Emerging Architectures (Zeta Architecture) |
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221 | (8) |
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229 | (1) |
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229 | (6) |
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235 | (72) |
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NoSQL Approaches to Biomedical Data Science |
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237 | (7) |
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Using Splunk for Data Analytics |
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244 | (6) |
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Statistical Analysis of Genomic Data with Hadoop |
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250 | (3) |
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Extracting and Transforming Genomic Data |
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253 | (3) |
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256 | (3) |
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Generating Master SNP Files for Cases and Controls |
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259 | (1) |
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Generating Gene Expression Files for Cases and Controls |
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260 | (1) |
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Cleaning Raw Data Using MapReduce |
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261 | (2) |
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Transpose Data Using Python |
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263 | (1) |
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Statistical Analysis Using Spark |
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264 | (4) |
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Hive Tables with Partitions |
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268 | (2) |
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270 | (1) |
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270 | (20) |
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Appendix: A Brief Statistics Primer |
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290 | (17) |
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Chapter 8 Next-Generation Cyberinfrastructures |
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307 | (30) |
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Next-Generation Cyber Capability |
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308 | (2) |
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NGCC Design and Infrastructure |
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310 | (17) |
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327 | (3) |
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330 | (5) |
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335 | (2) |
Appendix A The Research Data Management Survey: From Concepts to Practice |
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337 | (16) |
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Appendix B Central IT and Research Support |
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353 | (24) |
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Appendix C HPC Working Example: Using Parallelization Programs Such as GNU Parallel and OpenMP with Serial Tools |
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377 | (8) |
Appendix D HPC and Hadoop: Bridging HPC to Hadoop |
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385 | (6) |
Appendix E Bioinformatics + Docker: Simplifying Bioinformatics Tools Delivery with Docker Containers |
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391 | (8) |
Glossary |
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399 | (20) |
About the Author |
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419 | (2) |
About the Contributors |
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421 | (6) |
Index |
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427 | |