FAIR数据立方体,用于集成多组学数据分析的FAIR数据基础设施。

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY
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, Morris A Swertz, Martin Brandt, Alain J van Gool, Peter A C 't Hoen
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引用次数: 0

摘要

动机:我们正在见证分子分析(组学)数据量的巨大增长。多组学数据的集成具有挑战性。此外,人类多组学数据可能是隐私敏感的,可能被滥用于去匿名化和(重新)识别个人。因此,大多数生物医学数据都保存在安全和受保护的孤岛中。因此,在不侵犯数据来源的个人隐私的情况下重新使用这些数据仍然是一个挑战。可查找、可访问、可互操作和可重用(FAIR)数据的联邦分析是一种保护隐私的解决方案,可最佳地利用这些多组学数据并将其转换为可操作的知识。结果:荷兰x组学计划是一个国家大规模研究基础设施路线图,旨在有效整合x组学和外部数据集内生成的数据。为此,我们开发了FAIR数据立方体(FDCube),它采用并应用FAIR原则,帮助研究人员创建FAIR数据和元数据,方便其数据的重用,并使其数据分析工作流程透明化,同时确保数据安全和隐私。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FAIR Data Cube, a FAIR data infrastructure for integrated multi-omics data analysis.

Motivation: We 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.

Results: The 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.

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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
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