Privacy-preserved sharing and analysis of human genomic data


Fri Jan 17, 2014


Haixu Tang
School of Informatics and Computing, Indiana University, Bloomington


Genome Privacy (Linked Project)



While the debate is still on-going over the priority between the research uses of human genomic data versus the privacy of human subjects, privacy-preserving techniques are available for a balanced consideration of both of them. I will showcase a few examples, where customized privacy-preserving approaches have been adopted, implicitly or explicitly, for sharing different kinds of human genomic data. I will also discuss a generic data/computing model to facilitate privacy-preserved sharing and analysis of human genomic data, in which a data center  will offer a centralized analysis service on the human genomic data it hosts, execute the analysis programs submitted by data users, and control release of analysis outcomes to ensure the privacy of DNA donors from whom the genomic data were collected.



Haixu Tang is an associate professor in School of Informatics and Computing, and a co-Director of the Center for Genomics and Bioinformatics at Indiana University Bloomington. He received his Ph.D in Molecular Biology from Shanghai Institute of Biochemistry, Chinese Academy of Sciences in 1998, and worked as a postDoc associate in University of Southern California, and a project scientist in University of California, San Diego before joining Indiana University. Dr. Tang has been working on algorithmic problems in bioinformatics for over 20 years, and worked on genome privacy problems since 2008. He was a recipient of the NSF CAREER award in 2007, and an outstanding junior faculty award from Indiana University in 2009.



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