Evidence map›Paper›PMID 25521306›Full record

ArticleBMC medical informatics and decision making2014

Differentially private genome data dissemination through top-down specialization.

Shuang Wang, Noman Mohammed, Rui Chen

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Privacy-Enhancing Technologies in Biomedical Data Science.Annual review of biomedical data science · 2024
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Big Data Privacy in Biomedical Research.IEEE transactions on big data · 2020
    Article
  7. Review
  8. Protecting Genomic Data Privacy with Probabilistic Modeling.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2019
    Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. SCOTCH: Secure Counting Of encrypTed genomiC data using a Hybrid approach.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2017
    Article
  14. Article
  15. Article
  16. PREMIX: PRivacy-preserving EstiMation of Individual admiXture.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016
    Article
  17. PALME: PAtients Like My gEnome.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016
    Article
  18. Article
  19. Privacy-preserving GWAS analysis on federated genomic datasets.BMC medical informatics and decision making · 2015
    Article
  20. A community assessment of privacy preserving techniques for human genomes.BMC medical informatics and decision making · 2014
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Shuang Wang
Noman Mohammed
Rui Chen

Funding

San Diego Clinical and Translational Research InstituteUL1TR000100 · NCATS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI FIRESTEIN, GARY S · 2012 to 2015
$19.7M
iDASH: Integrating Data for Analysis, Anonymization, and SharingU54HL108460 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI OHNO-MACHADO, LUCILA · 2010 to 2015
$19.1M
Privacy preserving technologies for human genome data analysis and disseminationR01HG007078 · NHGRI · TRUSTEES OF INDIANA UNIVERSITY · PI TANG, HAIXU, WANG, XIAOFENG · 2013 to 2015
$886k
Protection of Records: Privacy (PReP) Technology for Medical ResearchR00LM011392 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JIANG, XIAOQIAN · 2013 to 2015
$650k
Protect Privacy of Healthcare Data in the CloudR21LM012060 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JIANG, XIAOQIAN · 2014 to 2015
$376k
Protecting the pRivacy Of Genomes in Research StudieS (PROGRESS)K99HG008175 · NHGRI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WANG, SHUANG · 2014 to 2015
$100k
NCATS NIH HHS UL1TR000100NHGRI NIH HHS K99 HG008175NHGRI NIH HHS K99HG008175NHGRI NIH HHS R01 HG007078NHGRI NIH HHS R01HG007078NHLBI NIH HHS U54HL108460NLM NIH HHS R00LM011392NLM NIH HHS R21LM012060
6 · The paper itself

Abstract

Advanced sequencing techniques make large genome data available at an unprecedented speed and reduced cost. Genome data sharing has the potential to facilitate significant medical breakthroughs. However, privacy concerns have impeded efficient genome data sharing. In this paper, we present a novel approach for disseminating genomic data while satisfying differential privacy. The proposed algorithm splits raw genome sequences into blocks, subdivides the blocks in a top-down fashion, and finally adds noise to counts to preserve privacy. The experimental results suggest that the proposed algorithm can retain certain data utility in terms of a high sensitivity.

Indexed as

AlgorithmsGenetic PrivacyGenome-Wide Association StudyHumansInformation Dissemination

Identifiers

PMID25521306
PMCPMC4290801

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.