Evidence map›Paper›PMID 38562180›Full record

Article... IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications : (TPS-ISA ...). IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications2023

Ensuring Trust in Genomics Research.

Erman Ayday, Jaideep Vaidya, Xiaoqian Jiang, Amalio Telenti

Abstract read
In one paragraph

Article in ... IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications : (TPS-ISA ...). IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Erman AydayDepartment of Computer and Data Sciences Case Western Reserve University Cleveland, OH.
Jaideep VaidyaManagement Science and Information Systems Department Rutgers University Newark, NJ.
Xiaoqian JiangDepartment of Data Science and Artificial Intelligence University of Texas - Health Houston, TX.
Amalio TelentiDept. of Integrative Structural and Computational Biology Scripps Institute La Jolla, CA.

Funding

Ethics Core (FABRIC)U54HG012510 · NHGRI · YALE UNIVERSITY · PI OHNO-MACHADO, LUCILA · 2022 to 2025
$11.2M
Accelerating Genomic Data Sharing and Collaborative Research with Privacy ProtectionR01LM014520 · NLM · CASE WESTERN RESERVE UNIVERSITY · PI Erman Ayday, Xiaoqian Jiang · 2023 to 2026
$2.6M
Decentralized differentially-private methods for dynamic data release and analysisR01LM013712 · NLM · YALE UNIVERSITY · PI JIANG, XIAOQIAN, OHNO-MACHADO, LUCILA · 2022 to 2025
$2.5M
Supplement for high performance compute clustersR35GM134927 · NIGMS · RUTGERS THE STATE UNIV OF NJ NEWARK · PI VAIDYA, JAIDEEP · 2020 to 2024
$2.1M
Privacy Challenges of Genomic Data-Sharing Beacons and SolutionsR01LM013429 · NLM · CASE WESTERN RESERVE UNIVERSITY · PI AYDAY, ERMAN · 2020 to 2023
$1.2M
NHGRI NIH HHS U54 HG012510NIGMS NIH HHS R35 GM134927NLM NIH HHS R01 LM013429NLM NIH HHS R01 LM013712NLM NIH HHS R01 LM014520
6 · The paper itself

Abstract

Reproducibility, transparency, representation, and privacy underpin the trust on genomics research in general and genome-wide association studies (GWAS) in particular. Concerns about these issues can be mitigated by technologies that address privacy protection, quality control, and verifiability of GWAS. However, many of the existing technological solutions have been developed in isolation and may address one aspect of reproducibility, transparency, representation, and privacy of GWAS while unknowingly impacting other aspects. As a consequence, the current patchwork of technological tools only partially and in an overlapping manner address issues with GWAS, sometimes even creating more problems. This paper addresses the progress in a field that creates technological solutions that augment the acceptance and security of population genetic analyses. The text identifies areas that are falling behind in technical implementation or where there is insufficient research. We make the case that a full understanding of the different GWAS settings, technological tools and new research directions can holistically address the requirements for the acceptance of GWAS.

Indexed as

genomics researchprivacyrepresentationtransparencytrust

Identifiers

PMID38562180
PMCPMC10981793

What OpenQuestion holds

Textmetadata
LicenceTDM
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.