@article{shi2017overview,
title = {An overview of human genetic privacy},
author = {Shi, Xinghua and Wu, Xintao},
year = {2017},
date = {2017-01-01},
journal = {Annals of the New York Academy of Sciences},
volume = {1387},
number = {1},
pages = {61--72},
publisher = {Wiley Online Library},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{chen2017princess,
title = {PRINCESS: Privacy-protecting Rare disease International Network Collaboration via Encryption through Software guard extensionS},
author = {Chen, Feng and Wang, Shuang and Jiang, Xiaoqian and Ding, Sijie and Lu, Yao and Kim, Jihoon and Sahinalp, S Cenk and Shimizu, Chisato and Burns, Jane C and Wright, Victoria J and others},
year = {2017},
date = {2017-01-01},
journal = {Bioinformatics},
pages = {btw758},
publisher = {Oxford Univ Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Raisaro2017,
title = {Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks},
author = {Raisaro, Jean Louis and Tramèr, Florian and Ji, Zhanglong and Bu, Diyue and Zhao, Yongan and Carey, Knox and Lloyd, David and Sofia, Heidi and Baker, Dixie and Flicek, Paul and Shringarpure, Suyash and Bustamante, Carlos and Wang, Shuang and Jiang, Xiaoqian and Ohno-Machado, Lucila and Tang, Haixu and Wang, XiaoFeng and Hubaux, Jean-Pierre},
url = {https://academic.oup.com/jamia/article/3038412/Addressing},
doi = {10.1093/jamia/ocw167},
issn = {1067-5027},
year = {2017},
date = {2017-01-01},
journal = {Journal of the American Medical Informatics Association},
volume = {0},
number = {0},
pages = {1--8},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{huang2017sqc,
title = {SQC: Secure Quality Control for Meta-Analysis of Genome-Wide Association Studies.},
author = {Huang, Zhicong and Lin, Huang and Fellay, Jacques and Kutalik, Zolt'an and Hubaux, Jean-Pierre},
year = {2017},
date = {2017-01-01},
journal = {Bioinformatics (Oxford, England)},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{mclaren2016privacy,
title = {Privacy-preserving genomic testing in the clinic: a model using HIV treatment},
author = {McLaren, Paul J. and Raisaro, Jean Louis and Aouri, Manel and Rotger, Margalida and Ayday, Erman and Bartha, István and Delgado, Maria B. and Vallet, Yannick and Günthard, Huldrych F. and Cavassini, Matthias and Furrer, Hansjakob and Doco-Lecompte, Thanh and Marzolini, Catia and Schmid, Patrick and Di Benedetto, Caroline and Decosterd, Laurent A. and Fellay, Jacques and Hubaux, Jean-Pierre and Telenti, Amalio and Study, ;the Swiss HIV Cohort},
url = {http://www.nature.com/doifinder/10.1038/gim.2015.167},
doi = {10.1038/gim.2015.167},
issn = {1098-3600},
year = {2016},
date = {2016-08-01},
journal = {Genetics in Medicine},
volume = {18},
number = {8},
pages = {814--822},
publisher = {Nature Publishing Group},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{shimizu2016efficient,
title = {Efficient privacy-preserving string search and an application in genomics},
author = {Shimizu, Kana and Nuida, Koji and R"atsch, Gunnar},
year = {2016},
date = {2016-01-01},
journal = {Bioinformatics},
volume = {32},
number = {11},
pages = {1652--1661},
publisher = {Oxford Univ Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@inproceedings{namazi2016dynamic,
title = {Dynamic Privacy-Preserving Genomic Susceptibility Testing},
author = {Namazi, Mina and Troncoso-Pastoriza, Juan Ram'on and P'erez-Gonz'alez, Fernando},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security},
pages = {45--50},
organization = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@article{simmons2016realizing,
title = {Realizing privacy preserving genome-wide association studies},
author = {Simmons, Sean and Berger, Bonnie},
year = {2016},
date = {2016-01-01},
journal = {Bioinformatics},
volume = {32},
number = {9},
pages = {1293--1300},
publisher = {Oxford Univ Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Simmons201654,
title = {Enabling Privacy-Preserving GWASs in Heterogeneous Human Populations},
author = {Simmons, Sean and Sahinalp, Cenk and Berger, Bonnie},
year = {2016},
date = {2016-01-01},
journal = {Cell Systems},
volume = {3},
number = {1},
pages = {54 - 61},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{wang2016healer,
title = {HEALER: Homomorphic computation of ExAct Logistic rEgRession for secure rare disease variants analysis in GWAS},
author = {Wang, Shuang and Zhang, Yuchen and Dai, Wenrui and Lauter, Kristin and Kim, Miran and Tang, Yuzhe and Xiong, Hongkai and Jiang, Xiaoqian},
year = {2016},
date = {2016-01-01},
journal = {Bioinformatics},
volume = {32},
number = {2},
pages = {211--218},
publisher = {Oxford Univ Press},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{wang2016genome,
title = {Genome privacy: challenges, technical approaches to mitigate risk, and ethical considerations in the United States},
author = {Wang, Shuang and Jiang, Xiaoqian and Singh, Siddharth and Marmor, Rebecca and Bonomi, Luca and Fox, Dov and Dow, Michelle and Ohno-Machado, Lucila},
year = {2016},
date = {2016-01-01},
journal = {Annals of the New York Academy of Sciences},
publisher = {Wiley Online Library},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{shi2016secure,
title = {Secure Multi-pArty Computation Grid LOgistic REgression (SMAC-GLORE)},
author = {Shi, Haoyi and Jiang, Chao and Dai, Wenrui and Jiang, Xiaoqian and Tang, Yuzhe and Ohno-Machado, Lucila and Wang, Shuang},
year = {2016},
date = {2016-01-01},
journal = {BMC Medical Informatics and Decision Making},
volume = {16},
number = {3},
pages = {89},
publisher = {BioMed Central},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@inproceedings{aziz2016secure,
title = {Secure and Efficient Multiparty Computation on Genomic Data},
author = {Aziz, Al and Momin, Md and Hasan, Mohammad Z and Mohammed, Noman and Alhadidi, Dima},
year = {2016},
date = {2016-01-01},
booktitle = {Proceedings of the 20th International Database Engineering & Applications Symposium},
pages = {278--283},
organization = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}

@article{Baker2016,
title = {Governance Through Privacy, Fairness, and Respect for Individuals.},
author = {Baker, Dixie B and Kaye, Jane and Terry, Sharon F},
url = {http://www.ncbi.nlm.nih.gov/pubmed/27141520 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4827784},
doi = {10.13063/2327-9214.1207},
issn = {2327-9214},
year = {2016},
date = {2016-01-01},
journal = {EGEMS (Washington, DC)},
volume = {4},
number = {2},
pages = {1207},
publisher = {Academy Health},
abstract = {INTRODUCTION Individuals have a moral claim to be involved in the governance of their personal data. Individuals' rights include privacy, autonomy, and the ability to choose for themselves how they want to manage risk, consistent with their own personal values and life situations. The Fair Information Practices principles (FIPPs) offer a framework for governance. Privacy-enhancing technology that complies with applicable law and FIPPs offers a dynamic governance tool for enabling the fair and open use of individual's personal data. PERCEPTIONS OF RISK Any governance model must protect against the risks posed by data misuse. Individual perceptions of risks are a subjective function involving individuals' values toward self, family, and society, their perceptions of trust, and their cognitive decision-making skills. THE HIPAA PRIVACY RULE PUTS SOME GOVERNANCE IN THE HANDS OF INDIVIDUALS Individual privacy protections and individuals' right to choose are codified in the HIPAA Privacy Rule, which attempts to strike a balance between the dual goals of information flow and privacy protection. The choices most commonly given individuals regarding the use of their health information are binary ("yes" or "no") and immutable. Recent federal recommendations and law recognize the need for granular, dynamic choices. BUILDING A GOVERNANCE FRAMEWORK BASED IN TRUST AVOIDING SURPRISES Individuals expect that they will govern the use of their own health and genomic data. Failure to build and maintain individuals' trust increases the likelihood that they will refuse to grant permission to access or use their data. The "no surprises principle" asserts that an individual's personal information should never be collected, used, transmitted, or disclosed in a way that would surprise the individual were she to learn about it. FAIR INFORMATION PRACTICES PRINCIPLES The FIPPs provide a powerful framework for enabling data sharing and use, while maintaining trust. We introduce the eight FIPPs adopted by the Department of Health and Human Services, and provide examples of their interpretation and implementation. REDUCING RISK THROUGH CONSUMER ENGAGEMENT Privacy risk and health risk can be reduced by giving consumers control, autonomy, and transparency, and by engaging them in managing their own health. Explicit "consent" may not always be necessary - the FIPPs offer multiple ways to engender trust and avoid surprises.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{Wang2016,
title = {Big Data Privacy in Biomedical Research},
author = {Wang, Shuang and Bonomi, Luca and Dai, Wenrui and Chen, Feng and Cheung, Cynthia and Bloss, Cinnamon S. and Cheng, Samuel and Jiang, Xiaoqian},
url = {http://ieeexplore.ieee.org/document/7565504/},
doi = {10.1109/TBDATA.2016.2608848},
issn = {2332-7790},
year = {2016},
date = {2016-01-01},
journal = {IEEE Transactions on Big Data},
pages = {1--1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}