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Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

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The International HapMap Project

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Encoded evidence: DNA in forensic analysis

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Large-scale genotyping of complex DNA

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Developing a SNP panel for forensic identification of individuals

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Analysis and interpretation of mixed forensic stains using DNA STR profiling

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Parentage analysis with genetic markers in natural populations. I. The expected proportion of offspring with unambiguous paternity.

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Single nucleotide polymorphisms over the entire mtDNA genome that increase the power of forensic testing in Caucasians

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Interpreting DNA Mixtures

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Identification of the Genetic Basis for Complex Disorders by Use of Pooling-Based Genomewide Single-Nucleotide–Polymorphism Association Studies

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General considerations for integrating pharmacogenomics into mainstream medical practice

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Private Computation of Phylogenetic Trees Based on Quantum Technologies

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An in-depth examination of requirements for disclosure risk assessment

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Legal aspects of privacy-enhancing technologies in genome-wide association studies and their impact on performance and feasibility

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ENABLING HIGH-THROUGHPUT GENOTYPE-PHENOTYPE ASSOCIATIONS IN THE EPIDEMIOLOGIC ARCHITECTURE FOR GENES LINKED TO ENVIRONMENT (EAGLE) PROJECT AS PART OF THE POPULATION ARCHITECTURE USING GENOMICS AND EPIDEMIOLOGY (PAGE) STUDY

Bush, W. S., BOSTON, J., Pendergrass, S. A., Dumitrescu, L. C., Goodloe, R., Brown-Gentry, K. D., Wilson, S., McClellan, B., Torstenson, E. S., Basford, M., et al. (2012) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447973_0037 · Cited by 13

Managing the Introduction of Biobanks to Potential Participants: Lessons from a Deliberative Public Forum

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Patient Awareness and Approval for an Opt-Out Genomic Biorepository

Brothers, K. B., Westbrook, M. J., Wright, M. F., Myers, J. A., Morrison, D. R., Madison, J. L., Pulley, J. M., & Clayton, E. W. (2013) · Personalized Medicine · doi:10.2217/pme.13.34 · Cited by 13

Addressing data privacy in matched studies via virtual pooling

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DNA Motif Finding Method Without Protection Can Leak User Privacy

Wu, X., Wang, H., Shi, M., Wang, A., & Xia, K. (2019) · IEEE Access · doi:10.1109/access.2019.2947261 · Cited by 13

DyPS: Dynamic, Private and Secure GWAS

Pascoal, T. A., Decouchant, J., Boutet, A., & Verı́ssimo, P. (2021) · Proceedings on Privacy Enhancing Technologies · doi:10.2478/popets-2021-0025 · Cited by 13

Unexpected Information Leakage of Differential Privacy Due to the Linear Property of Queries

Huang, W. C., Zhou, S., & Liao, Y. (2021) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2021.3075843 · Cited by 13

QuerySnout

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Economic Analysis of the Digital Economy

Avi Goldfarb, B., Greenstein, S. M., & Tucker, C. E. (2015) · University of Chicago Press eBooks · doi:10.7208/chicago/9780226206981.001.0001 · Cited by 84

You Are Born with Your Genes: Justice and Protection against Discrimination in the Use of Genetic Information

Francis, L. P. (2010) · Mount Sinai Journal of Medicine A Journal of Translational and Personalized Medicine · doi:10.1002/msj.20170 · Cited by 13

Bodies of Data: Genomic Data and Bioscience Data Sharing

Ossorio, P. N. (2011) · Social research · doi:10.1353/sor.2011.0029 · Cited by 13

Comparison of Microbial Community and Metabolites in Four Stomach Compartments of Myostatin-Gene-Edited and Non-edited Cattle

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Opportunities and Challenges Provided by Cloud Repositories for Bioinformatics‐Enabled Drug Discovery

Dalpé, G., & Joly, Y. (2014) · Drug Development Research · doi:10.1002/ddr.21211 · Cited by 12

Specific Legislation on Biobanks in Spain

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Genome-wide association studies - A summary for theclinical gastroenterologist

Melum, E., Franke, A., & Karlsen, T. H. (2009) · World Journal of Gastroenterology · doi:10.3748/wjg.15.5377 · Cited by 13

Regulatory aspects of genetic research with residual human tissue: Effective and efficient data coding

Schmidt, M. K., Vermeulen, E., Tollenaar, R. A. E. M., Veer, L. J. V., & Leeuwen, F. E. V. (2009) · European Journal of Cancer · doi:10.1016/j.ejca.2009.03.008 · Cited by 12

Biomedical Informatics Methods for Personalized Medicine and Participatory Health

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High-accuracy low-cost privacy-preserving federated learning in IoT systems via adaptive perturbation

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Privacy-preserving federated genome-wide association studies via dynamic sampling

Wang, X., Dervishi, L., Li, W., Ayday, E., Jiang, X., & Vaidya, J. S. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad639 · Cited by 12

Using aggregate human genome data for individual identification

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Cohorts and consortia conference: a summary report (Banff, Canada, June 17–19, 2009)

Boffetta, P., Colditz, G. A., Potter, J. D., Kolonel, L. N., Robson, P. J., Malekzadeh, R., Seminara, D., Goode, E. L., Yoo, K., Demers, P. A., et al. (2011) · Cancer Causes & Control · doi:10.1007/s10552-010-9717-0 · Cited by 12

Privacy protection in government data sharing: an improved LDP-based approach

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Combination of Multiple Microsatellite Analysis and Genome-Wide SNP Genotyping Helps to Solve Wildlife Crime: A Case Study of Poaching of a Caucasian tur (Capra caucasica) in Russian Mountain National Park

Rodionov, A. N., Deniskova, T. E., Dotsev, A. V., Volkova, V. V., Petrov, S. N., Kharzinova, V. R., Koshkina, O. A., Abdelmanova, A. S., Solovieva, A. D., Shakhin, A. V., et al. (2021) · Animals · doi:10.3390/ani11123416 · Cited by 12

Neurogenethics: An emerging discipline at the intersection of ethics, neuroscience, and genomics

Canli, T. (2015) · Applied & Translational Genomics · doi:10.1016/j.atg.2015.05.002 · Cited by 14

Optimal vocabulary selection approaches for privacy-preserving deep NLP model training for information extraction and cancer epidemiology

Yoon, H., Stanley, C. B., Christian, J. B., Klasky, H. B., Blanchard, A. E., Durbin, E. B., Wu, X., Stroup, A. M., Doherty, J. A., Schwartz, S. M., et al. (2022) · Cancer Biomarkers · doi:10.3233/cbm-210306 · Cited by 12

Protection of genomic data and the Australian Privacy Act: when are genomic data ‘personal information’?

Paltiel, M., Taylor, M., & Newson, A. J. (2023) · International Data Privacy Law · doi:10.1093/idpl/ipad002 · Cited by 12

Facilitating Federated Genomic Data Analysis by Identifying Record Correlations while Ensuring Privacy

Dervishi, L., Wang, X., Li, W., Halimi, A., Vaidya, J. S., Jiang, X., & Ayday, E. (2022) · PubMed Central · doi:10.48550/arxiv.2203.05664 · Cited by 12

MoPe: Model Perturbation based Privacy Attacks on Language Models

Li, M., Wang, J., Wang, J., & Neel, S. (2023) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2023.emnlp-main.842 · Cited by 25

A private DNA motif finding algorithm

Chen, R., Peng, Y. F., Choi, B. K. K., Xu, J., & Hu, H. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2013.12.016 · Cited by 12

NCI think tank concerning the identifiability of biospecimens and “omic” data

Weil, C. J., Mechanic, L. E., Green, T., Kinsinger, C. R., Lockhart, N. C., Nelson, S. A., Rodriguez, L. L., & Buccini, L. D. (2013) · Genetics in Medicine · doi:10.1038/gim.2013.40 · Cited by 12

Pathway Analysis of the Human Brain Transcriptome in Disease

Kavanagh, T., Mills, J. D., Kim, W. S., Halliday, G. M., & Janitz, M. (2012) · Journal of Molecular Neuroscience · doi:10.1007/s12031-012-9940-0 · Cited by 13

Empirical Bayes and semi-Bayes adjustments for a vast number of estimations

Strömberg, U. (2009) · European Journal of Epidemiology · doi:10.1007/s10654-009-9393-0 · Cited by 12

Privacy-Preserving Read Mapping Using Locality Sensitive Hashing and Secure Kmer VotingPreprint

Popic, V., & Batzoglou, S. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/046920 · Cited by 12

On the Sample Complexity of Privately Learning Unbounded High-Dimensional GaussiansPreprint

Aden-Ali, I., Ashtiani, H., & Kamath, G. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.09929 · Cited by 12

Is Private Learning Possible with Instance Encoding?Preprint

Carlini, N., Deng, S., Garg, S., Jha, S., Mahloujifar, S., Mahmoody, M., Song, S., Thakurta, A., & Tramèr, F. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.05315 · Cited by 37

Covariance-Aware Private Mean Estimation Without Private Covariance EstimationPreprint

Brown, G., Gaboardi, M., Smith, A., Ullman, J., & Zakynthinou, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.13329 · Cited by 12

GWAS advancements to investigate disease associations and biological mechanisms

Omidiran, O., Patel, A., Usman, S., Mhatre, I., Abdelhalim, H., DeGroat, W., Narayanan, R., Singh, K., Mendhe, D., & Ahmed, Z. (2024) · Clinical and Translational Discovery · doi:10.1002/ctd2.296 · Cited by 13

Data governance and open sharing in the fields of life sciences and medicine: A bibliometric analysis

Qiu, Y., & Hu, Z. (2025) · Digital Health · doi:10.1177/20552076251320302 · Cited by 14

Biobanking, Consent, and Certificates of Confidentiality: Does the ANPRM Muddy the Water?

Williams, B. A., & Wolf, L. E. (2013) · The Journal of Law Medicine & Ethics · doi:10.1111/jlme.12054 · Cited by 11

Implementation of the CDC translational informatics platform - from genetic variants to the national Swedish Rheumatology Quality Register

Abugessaisa, I., Gómez-Cabrero, D., Snir, O., Lindblad, S., Klareskog, L., Malmström, V., & Tegner, J. N. (2013) · Journal of Translational Medicine · doi:10.1186/1479-5876-11-85 · Cited by 11

A multi-institution evaluation of clinical profile anonymization

Heatherly, R. D., Rasmussen, L. V., Peissig, P. L., Pacheco, J. A., Harris, P. A., Denny, J. C., & Malin, B. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv154 · Cited by 12

Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks

Lin, S., Yin, Y. A., Jiang, X., Sahni, N., & Yi, S. S. (2016) · BioMed Research International · doi:10.1155/2016/6186281 · Cited by 12

Reporting Actionable Research Results: Shared Secrets Can Save Lives

Hunter, L., Hopfer, C. J., Terry, S. F., & Coors, M. E. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003958 · Cited by 11

Combined analysis of correlated data when data cannot be pooled

Jones, E. M., Sheehan, N. A., Gaye, A., Laflamme, P., & Burton, P. R. (2013) · Stat · doi:10.1002/sta4.19 · Cited by 11

A spectrum of sharing: maximization of information content for brain imaging data

Calhoun, V. D. (2015) · GigaScience · doi:10.1186/s13742-014-0042-5 · Cited by 11

Genomic Research with Organs and Tissues Originating from Transplant Donors: Ethical Considerations for the GTEx Project.

Lockhart, N. C., Smith, A. M., Carithers, L. J., & Weil, C. J. (2016) · PubMed · Cited by 11

Representation transfer for differentially private drug sensitivity prediction

Niinimäki, T., Heikkilä, M., Honkela, A., & Samuel Kaski, A. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz373 · Cited by 11

Illuminating the Dark or how to recover what should not be seen in FE-based classifiers

Carpov, S., Fontaine, C., Ligier, D., & Sirdey, R. (2020) · Proceedings on Privacy Enhancing Technologies · doi:10.2478/popets-2020-0015 · Cited by 13

Privacy-preserving chi-squared test of independence for small samples

Sei, Y., & Ohsuga, A. (2021) · BioData Mining · doi:10.1186/s13040-021-00238-x · Cited by 11

More practical differentially private publication of key statistics in GWAS

Yamamoto, A., & Shibuya, T. (2021) · Bioinformatics Advances · doi:10.1093/bioadv/vbab004 · Cited by 11

Preserving data privacy when using multi‐site data to estimate individualized treatment rules

Danieli, C., & Moodie, E. E. M. (2022) · Statistics in Medicine · doi:10.1002/sim.9318 · Cited by 12

Advanced Molecular Probes for Sequence-Specific DNA Recognition

Bertucci, A., Manicardi, A., & Corradini, R. (2012) · Soft and biological matter · doi:10.1007/978-94-007-1226-3_4 · Cited by 11

SCOTCH: Secure Counting Of encrypTed genomiC data using a Hybrid approach.

Wang, C., Jiang, Y., Mohammed, N., Chen, F., Jiang, X., Aziz, M. M. A., Sadat, M. N., & Wang, S. (2017) · PubMed Central · Cited by 11

Resistance effect of flavonols and toxicology analysis of hexabromocyclododecane based on soil-microbe-plant system

Zhang, X., Herger, A., Ren, Z., Li, X., & Cui, Z. (2020) · Chemosphere · doi:10.1016/j.chemosphere.2020.127248 · Cited by 11

Development of a fingerprinting panel using medically relevant polymorphisms

Cross, D. S., Ivacic, L. C., & McCarty, C. A. (2009) · BMC Medical Genomics · doi:10.1186/1755-8794-2-17 · Cited by 11

Privacy-Preserving Data Sharing for Genome-Wide Association StudiesPreprint

Uhler, C., Slavković, A., & Fienberg, S. E. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1205.0739 · Cited by 11

Trade-offs and Guarantees of Adversarial Representation Learning for Information ObfuscationPreprint

Zhao, H., Chi, J., Tian, Y., & Gordon, G. J. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1906.07902 · Cited by 14

The influence of dropout and residual connection against membership inference attacks on transformer model: a neuro generative disease case study

Hamida, S. B., Hamida, S. B., Snoun, A., Jemai, O., & Jemai, A. (2023) · Multimedia Tools and Applications · doi:10.1007/s11042-023-16126-x · Cited by 10

STrengthening the REporting of Genetic Association studies (STREGA)—an extension of the STROBE statement

Little, J., Higgins, J. P. T., Ioannidis, J. P. A., Moher, D., Gagnon, F., von Elm, E. B., Khoury, M. J., Cohen, B., Smith, G. D., Grimshaw, J., et al. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195398441.003.0010 · Cited by 10

Federated generalized linear mixed models for collaborative genome-wide association studies

Li, W., Chen, H., Jiang, X., & Harmanci, A. O. (2023) · iScience · doi:10.1016/j.isci.2023.107227 · Cited by 10

Promoting Data Sharing: The Moral Obligations of Public Funding Agencies

Wendelborn, C., Anger, M., & Schickhardt, C. (2024) · Science and Engineering Ethics · doi:10.1007/s11948-024-00491-3 · Cited by 13

One Size Doesn't Fit All: Measuring Individual Privacy in Aggregate Genomic Data

Simmons, S., & Berger, B. (2015) · IEEE Security and Privacy Workshops (SPW) · doi:10.1109/spw.2015.25 · Cited by 10

Expanded Genetic Codes in Next Generation Sequencing Enable Decontamination and Mitochondrial Enrichment

McKernan, K. J., Spangler, J., Zhang, L., Tadigotla, V. R., McLaughlin, S., Warner, J. B., Zare, A., & Boles, R. G. (2014) · PLoS ONE · doi:10.1371/journal.pone.0096492 · Cited by 10

Comprehensive Genomic Studies

McDonald, S. A., Mardis, E. R., Ota, D. M., Watson, M. A., Pfeifer, J. D., & Green, J. M. (2012) · American Journal of Clinical Pathology · doi:10.1309/ajcpxba69lnscvmh · Cited by 10

Ensuring privacy in the study of pathogen genetics

Mehta, S. R., Vinterbo, S. A., & Little, S. J. (2014) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(14)70016-7 · Cited by 10

Hidden-service statistics reported by relays

Goulet, D., Johnson, A., Kadianakis, G., & Loesing, K. (2015) · Cited by 10

What’s Wrong with the Right to Genetic Privacy: Beyond Exceptionalism, Parochialism and Adventitious Ethics

Goodman, B. (2016) · Law, governance and technology series · doi:10.1007/978-3-319-33525-4_7 · Cited by 12

Providing accurate models across private partitioned data: Secure maximum likelihood estimation

Snoke, J., Brick, T. R., Slavković, A., & Hunter, M. D. (2018) · The Annals of Applied Statistics · doi:10.1214/18-aoas1171 · Cited by 10

Inference attacks on genomic privacy with an improved HMM and an RCNN model for unrelated individuals

Ding, H., Tian, Y., Peng, C., Zhang, Y., & Xiang, S. (2019) · Information Sciences · doi:10.1016/j.ins.2019.09.036 · Cited by 10

Measuring Membership Privacy on Aggregate Location Time-Series

Pyrgelis, A., Troncoso, C., & Cristofaro, E. D. (2020) · ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS) · doi:10.1145/3393691.3394200 · Cited by 12

Haplotype-based membership inference from summary genomic data

Bu, D., Wang, X., & Tang, H. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab305 · Cited by 10

Genome Privacy and Trust

Gürsoy, G. (2022) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-122120-021311 · Cited by 12

Portable Approaches to Informed Consent and Open Data

WILBANKS, J. T. (2014) · Cambridge University Press eBooks · doi:10.1017/cbo9781107590205.014 · Cited by 10

NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data

Senanayake, N., Podschwadt, R., Takabi, D., Calhoun, V. D., & Plis, S. (2021) · Neuroinformatics · doi:10.1007/s12021-021-09525-8 · Cited by 10

Quantifying Membership Inference Vulnerability via Generalization Gap and Other Model MetricsPreprint

Bentley, J., Gibney, D., Hoppenworth, G., & Jha, S. K. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2009.05669 · Cited by 10

Human microbiome privacy risks associated with summary statistics

Cho, J.-C. (2021) · PLoS ONE · doi:10.1371/journal.pone.0249528 · Cited by 9

Privacy Auditing in Differential Private Machine Learning: The Current Trends

Namatēvs, I., Sudars, K., Ņikuļins, A., & Ozols, K. (2025) · Applied Sciences · doi:10.3390/app15020647 · Cited by 14

Interdisciplinary and Transferable Concepts in Bioinformatics Education: Observations and Approaches From a UK MSc Course

Johnston, I. G., Slater, M. W., & Cazier, J. (2022) · Frontiers in Education · doi:10.3389/feduc.2022.826951 · Cited by 9

Privacy Risk Assessment of Training Data in Machine Learning

Bai, Y., Fan, M., Li, Y., & Xie, C. (2022) · International Conference on Communications · doi:10.1109/icc45855.2022.9839062 · Cited by 9

Regulation of Biobanks in France

Rial‐Sebbag, E., & Pigeon, A. (2015) · The Journal of Law Medicine & Ethics · doi:10.1111/jlme.12317 · Cited by 9

Low-Level DNA and Complex Mixtures

Butler, J. M. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-405213-0.00007-5 · Cited by 9

Health privacy in genetic research: Populations and persons

Knoppers, B. M., & Abdul-Rahman, M. H. (2009) · Politics and the Life Sciences · doi:10.2990/28_2_99 · Cited by 9

Taking DNA from the dead

McGuire, A. L., Majumder, M. A., Halpern, S. D., Swindell, J. S., Yaeger, L. V., Gibbs, R. A., & Wheeler, T. M. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2792 · Cited by 9

Personalizing Rare Disease Research: How Genomics is Revolutionizing the Diagnosis and Treatment of Rare Disease

Dolled-Filhart, M. P., Lordemann, A., Dahl, W. B., Haraksingh, R., Ou-Yang, C.-W., & Lin, J. (2012) · Personalized Medicine · doi:10.2217/pme.12.97 · Cited by 10

Newspaper coverage of biobanks

Ogbogu, U., Toews, M., Ollenberger, A., Borry, P., Nobile, H., Bergmann, M. M., & Caulfield, T. (2014) · PeerJ · doi:10.7717/peerj.500 · Cited by 9

Ethically sustainable governance in the biobanking of eggs and embryos for research

Stroud, K., & O’Doherty, K. C. (2015) · Bioethics News · doi:10.1007/s40592-015-0047-6 · Cited by 9

PriSearch

Riazi, M. S., Songhori, E. M., & Koushanfar, F. (2017) · ACM/IEEE Design Automation Conference (DAC) · doi:10.1145/3061639.3062305 · Cited by 9

Oncological Ligand-Target Binding Systems and Developmental Approaches for Cancer Theranostics

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The Impact of Assisted Reproduction on Socio-Cultural Values and Social Norms

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