Responsible Genomic Data Sharing
Challenges and Approaches
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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.
Key Features
- 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
Readership
Active clinical and translational researchers across genetics, genomics, molecular biology, molecular diagnostics, and bioinformatics; pharmacologists; genetic counselors. Students at the graduate level and above in genetics, genomics, bioinformatics, molecular biology, and pharmaceutical science
Table of Contents
Section I: Privacy Challenges in Genomic Data Sharing
1. Criticality of Data Sharing in Genomic Research & Public views of genomic data sharing
Gamze Gursoy
2. Genomic data access policy models
Stephanie Dyke
3. Information leaks in aggregate genomic data, inference attacks
Erman Ayday
4. Genealogical search using whole genome genotype profiles
Yuan Wei, Ryan Lewis, Ardalan Naseri, Shaojie Zhang, Degui ZhiSection II: Privacy-Preserving Techniques for Responsible Genomic Data Sharing
5. Homomorphic encryption
Kim Laine
6. Secure Multiparty Computing (MPC)
Yan Huang
7. Game-Theoretic Approaches (for Genomic Privacy)
Zhiyu Wan
8. Hardware (SGX)
Somnath Chakrabarti, Thomas Knauth, Dmitrii Kuvaiskii, Michael Steiner and Mona Vij
Product details
- No. of pages: 210
- Language: English
- Copyright: © Academic Press 2020
- Published: March 14, 2020
- Imprint: Academic Press
- Paperback ISBN: 9780128161975
- eBook ISBN: 9780128163399
About the Editors
Xiaoqian Jiang
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.
Affiliations and Expertise
Associate Professor, Carnegie Mellon University, School of Computer Science
Haixu Tang
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.
Affiliations and Expertise
Professor, Department of Computer Science, Indiana University, Bloomington, IN, USA