A data management infrastructure for the integration of imaging and omics data in life sciences.
Data integration
Data management infrastructure
Distributed systems
Imaging
Metadata models
Omics
Service oriented architecture
Journal
BMC bioinformatics
ISSN: 1471-2105
Titre abrégé: BMC Bioinformatics
Pays: England
ID NLM: 100965194
Informations de publication
Date de publication:
07 Feb 2022
07 Feb 2022
Historique:
received:
26
06
2020
accepted:
21
01
2022
entrez:
8
2
2022
pubmed:
9
2
2022
medline:
10
2
2022
Statut:
epublish
Résumé
As technical developments in omics and biomedical imaging increase the throughput of data generation in life sciences, the need for information systems capable of managing heterogeneous digital assets is increasing. In particular, systems supporting the findability, accessibility, interoperability, and reusability (FAIR) principles of scientific data management. We propose a Service Oriented Architecture approach for integrated management and analysis of multi-omics and biomedical imaging data. Our architecture introduces an image management system into a FAIR-supporting, web-based platform for omics data management. Interoperable metadata models and middleware components implement the required data management operations. The resulting architecture allows for FAIR management of omics and imaging data, facilitating metadata queries from software applications. The applicability of the proposed architecture is demonstrated using two technical proofs of concept and a use case, aimed at molecular plant biology and clinical liver cancer research, which integrate various imaging and omics modalities. We describe a data management architecture for integrated, FAIR-supporting management of omics and biomedical imaging data, and exemplify its applicability for basic biology research and clinical studies. We anticipate that FAIR data management systems for multi-modal data repositories will play a pivotal role in data-driven research, including studies which leverage advanced machine learning methods, as the joint analysis of omics and imaging data, in conjunction with phenotypic metadata, becomes not only desirable but necessary to derive novel insights into biological processes.
Sections du résumé
BACKGROUND
BACKGROUND
As technical developments in omics and biomedical imaging increase the throughput of data generation in life sciences, the need for information systems capable of managing heterogeneous digital assets is increasing. In particular, systems supporting the findability, accessibility, interoperability, and reusability (FAIR) principles of scientific data management.
RESULTS
RESULTS
We propose a Service Oriented Architecture approach for integrated management and analysis of multi-omics and biomedical imaging data. Our architecture introduces an image management system into a FAIR-supporting, web-based platform for omics data management. Interoperable metadata models and middleware components implement the required data management operations. The resulting architecture allows for FAIR management of omics and imaging data, facilitating metadata queries from software applications. The applicability of the proposed architecture is demonstrated using two technical proofs of concept and a use case, aimed at molecular plant biology and clinical liver cancer research, which integrate various imaging and omics modalities.
CONCLUSIONS
CONCLUSIONS
We describe a data management architecture for integrated, FAIR-supporting management of omics and biomedical imaging data, and exemplify its applicability for basic biology research and clinical studies. We anticipate that FAIR data management systems for multi-modal data repositories will play a pivotal role in data-driven research, including studies which leverage advanced machine learning methods, as the joint analysis of omics and imaging data, in conjunction with phenotypic metadata, becomes not only desirable but necessary to derive novel insights into biological processes.
Identifiants
pubmed: 35130839
doi: 10.1186/s12859-022-04584-3
pii: 10.1186/s12859-022-04584-3
pmc: PMC8822871
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
61Subventions
Organisme : Deutsche Forschungsgemeinschaft
ID : SFB/TR 209
Organisme : Deutsche Forschungsgemeinschaft
ID : SFB 1101
Organisme : Deutsche Forschungsgemeinschaft
ID : SFB/TR 261
Organisme : Deutsche Forschungsgemeinschaft
ID : KO-2313/6-1
Organisme : Deutsche Forschungsgemeinschaft
ID : KO-2313/2
Organisme : Exzellenzcluster Mikrobiologie
ID : EXC-2124
Organisme : Bundesministerium für Bildung und Forschung
ID : 01ZX1301F
Organisme : Bundesministerium für Bildung und Forschung
ID : 01ZX1301A
Organisme : Bundesministerium für Bildung und Forschung
ID : 01ZX1601G
Informations de copyright
© 2022. The Author(s).
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