Responsible Genomic Data Sharing

  • ID: 4746000
  • Book
  • 384 Pages
  • Elsevier Science and Technology
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Responsible Genomic Data Sharing: Challenges and Approaches brings together international experts in genomics research, bioinformatics and digital security who analyze common challenges in genomic data sharing, privacy preserving technologies, and best practices for large-scale genomic data sharing. Practical case studies, including the Global Alliance for Genomics and Health, the Beacon Network, and the Matchmaker Exchange, are discussed in-depth, illuminating pathways forward for new genomic data sharing efforts across research and clinical practice, industry and academia.

  • Addresses privacy preserving technologies and how they can be applied to enable responsible genomic data sharing
  • Employs illustrative case studies and analyzes emerging genomic data sharing efforts, common challenges and lessons learned
  • Features chapter contributions from international experts in responsible approaches to genomic data sharing
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Section I: Privacy Challenges in Genomic Data Sharing 1. Criticality of data sharing in genomic research 2. Public views of genomic data sharing 3. Ethics issues in genomic data sharing (informed consent, patient-centric view, etc) 4. models of sharing genomic data (controlled access, registered users and open access) 5. Information leaks in aggregate genomic data, inference attacks

Section II: Privacy-Preserving Techniques for Responsible Genomic Data Sharing 6. Overview 7. Homomorphic encryption 8. SMC 9. DP, LLR test, etc 10. Game theory approach 11. Hardware (SGX)

Section III: Practices of Responsible Genomic Data Sharing 12. Genomic data sharing within large genomic research consortium (e.g, ICGC) 13. GA4GH: Building tools and standards for responsible genomic data sharing 14. Beacon 15. Matchmaker exchange for rare disease patients 16. ExAC (exome consortium)

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Jiang, Xiaoqian
Dr. Jiang is a Christopher Sarofim associate professor and center director for health security and phenotyping in the School of Biomedical Informatics (SBMI) at The University of Texas Health Science Center at Houston (UTHealth). Before joining UThealth, he was an associate professor with tenure in the Department of Biomedical Informatics (DBMI) at UCSD. He is an associate editor of BMC Medical Informatics and Decision Making and served as the editorial board member of Journal of American Medical Informatics Association. He works primarily in health data privacy and predictive models in biomedicine. He received CPRIT Rising Stars and UT Stars awards and best and distinguished paper awards from American Medical Informatics Association (AMIA) Joint Summits on Translational Science (2012, 2013, 2016). He is one of the organizers of the iDASH Genome Privacy Workshops, which was reported by Nature News and GenomeWeb.
Tang, Haixu
Dr. Haixu Tang is a Professor of Computer Science and the Director of Data Science Academic Programs in School of Informatics, Computing, and Engineering at Indiana University, Bloomington. His primary research interests include algorithmic statistical problems in genomics and proteomics, and has been working on genome privacy protection algorithms since 2008. He received the NSF CAREER Award in 2007, and the PETS award for his work in genome privacy in 2009. He is one of the organizers of the iDASH Genome Privacy Workshops.
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