A data management infrastructure for the integration of imaging and omics data in life sciences
Luis Eugenio 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 P. Malek,Klaus Harter,Michael Bitzer,Sven Nahnsen +15 more
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TLDR
In this paper , the authors propose a Service Oriented Architecture approach for integrated management and analysis of multi-omics and biomedical imaging data, and exemplify its applicability for basic biology research and clinical studies.Abstract:
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. read more
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Web-Based Application for Biomedical Image Registry, Analysis, and Translation (BiRAT)
Rahul Pemmaraju,Robert E. Minahan,E I Wang,Kornél Schadl,Heike E. Daldrup-Link,Frezghi Habte +5 more
TL;DR: A web-based server application that is designed to reflect the actual experimentation workflow maintaining detailed records of both individual images and experimental data relevant to specific studies and/or projects is developed.
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A Survey on the Role of Artificial Intelligence in Biobanking Studies: A Systematic Review
TL;DR: AI’s role in the development of biobanks in the healthcare industry, systematically, and Translational bioinformatics probably represent a future leader in precision medicine.
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Multi-Omics Profiling for Health
Mohan Babu,Michael Snyder +1 more
TL;DR: In this article , a review highlights current and emerging multi-omics modalities for precision health and discusses applications in the following areas: genetic variation, cardio-metabolic diseases, cancer, infectious diseases, organ transplantation, pregnancy, and longevity/aging.
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medna-metadata: an open-source data management system for tracking environmental DNA samples and metadata
Melissa Kimble,S. Allers,K. Campbell,Chaofan Chen,Laura M. Jackson,Benjamin L. King,Samantha Silverbrand,Geneva York,Kate Beard +8 more
TL;DR: Medna-metadata is presented, an open-source, modular system that aligns with Findable, Accessible, Interoperable, and Reusable guiding principles that support scholarly data reuse and the database and application development of a standardized metadata collection structure that encapsulates critical aspects of field data collection, wet lab processing, and bioinformatic analysis.
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Research data management for bioimaging: the 2021 NFDI4BIOIMAGE community survey.
Christian Schmidt,Janina Hanne,Josh Moore,Christian Meesters,Elisa Ferrando-May,Stefanie Weidtkamp-Peters +5 more
TL;DR: The importance and value of bioimaging RDM and data sharing was highlighted in a survey conducted by as mentioned in this paper , where the authors created a questionnaire tailored to relevant topics of the bio-imaging community, including specific questions on bioimages methods and bioimage analysis, as well as more general questions on RDM principles and tools.
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