Academic Journal
A data management infrastructure for the integration of imaging and omics data in life sciences
| العنوان: | A data management infrastructure for the integration of imaging and omics data in life sciences |
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| المؤلفون: | Luis Kuhn Cuellar, Andreas Friedrich, Gisela Gabernet, Luis de la Garza, Sven Fillinger, Adrian Seyboldt, Tobias Koch, Sven zur Oven-Krockhaus, Friederike Wanke, Sandra Richter, Wolfgang M. Thaiss, Marius Horger, Nisar Malek, Klaus Harter, Michael Bitzer, Sven Nahnsen |
| المصدر: | BMC Bioinformatics, Vol 23, Iss 1, Pp 1-20 (2022) |
| بيانات النشر: | BMC, 2022. |
| سنة النشر: | 2022 |
| المجموعة: | LCC:Computer applications to medicine. Medical informatics LCC:Biology (General) |
| مصطلحات موضوعية: | Data integration, Imaging, Omics, Metadata models, Distributed systems, Service oriented architecture, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5 |
| الوصف: | Abstract 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 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 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. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1471-2105 |
| Relation: | https://doaj.org/toc/1471-2105 |
| DOI: | 10.1186/s12859-022-04584-3 |
| URL الوصول: | https://doaj.org/article/8099a30aaa70462e98a8dcdcaa428906 |
| رقم الانضمام: | edsdoj.8099a30aaa70462e98a8dcdcaa428906 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 14712105 |
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| DOI: | 10.1186/s12859-022-04584-3 |