Evidence map›Paper›PMID 39732721›Full record

ArticleJournal of biomedical semantics2024

FAIR Data Cube, a FAIR data infrastructure for integrated multi-omics data analysis.

Xiaofeng Liao, Thomas H A Ederveen, Anna Niehues, Casper de Visser, Junda Huang, Firdaws Badmus, Cenna Doornbos, Yuliia Orlova, Purva Kulkarni, K Joeri van der Velde and 4 more

Abstract read
In one paragraph

Article in Journal of biomedical semantics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

14 authors.

Xiaofeng LiaoMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands. XiaoFeng.Liao@radboudumc.nl.
Thomas H A EderveenMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands.
Anna NiehuesMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands.
Casper de VisserMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands.
Junda HuangMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands.
Firdaws BadmusMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands.
Cenna DoornbosMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands.
Yuliia OrlovaSURF, Science Park 140, 1098 XG, Amsterdam, The Netherlands.
Purva KulkarniMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands.
K Joeri van der VeldeGenomics Coordination Center, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands.
Morris A SwertzGenomics Coordination Center, University of Groningen and University Medical Center Groningen, Groningen, The Netherlands.
Martin BrandtSURF, Science Park 140, 1098 XG, Amsterdam, The Netherlands.
Alain J van GoolTranslational Metabolic Laboratory, Department of Laboratory Medicine, Radboud University Medical Center, Nijmegen, The Netherlands.
Peter A C 't HoenMedical BioSciences Department, Radboud University Medical Center, Nijmegen, The Netherlands. Peter-Bram.tHoen@radboudumc.nl.

Funding

Horizon 2020 Framework Programme 825575LSH HealthHolland Trusted World of CoronaNederlandse Organisatie voor Wetenschappelijk Onderzoek 184.034.019NWO open science fund 17703
6 · The paper itself

Abstract

motivationWe are witnessing an enormous growth in the amount of molecular profiling (-omics) data. The integration of multi-omics data is challenging. Moreover, human multi-omics data may be privacy-sensitive and can be misused to de-anonymize and (re-)identify individuals. Hence, most biomedical data is kept in secure and protected silos. Therefore, it remains a challenge to re-use these data without infringing the privacy of the individuals from which the data were derived. Federated analysis of Findable, Accessible, Interoperable, and Reusable (FAIR) data is a privacy-preserving solution to make optimal use of these multi-omics data and transform them into actionable knowledge.

resultsThe Netherlands X-omics Initiative is a National Roadmap Large-Scale Research Infrastructure aiming for efficient integration of data generated within X-omics and external datasets. To facilitate this, we developed the FAIR Data Cube (FDCube), which adopts and applies the FAIR principles and helps researchers to create FAIR data and metadata, to facilitate re-use of their data, and to make their data analysis workflows transparent, and in the meantime ensure data security and privacy.

Indexed as

Data AnalysisComputer SecurityGenomicsHumansMultiomicsData sovereigntyFAIRFAIR Data CubeFederated analysisMetadataMulti-omics

Identifiers

PMID39732721
PMCPMC11681678

What OpenQuestion holds

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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.