ArticleBioinformatics (Oxford, England)2019
Interoperable and scalable data analysis with microservices: applications in metabolomics.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed.
- Metabolomics: An Emerging "Omics" Platform for Systems Biology and Its Implications for Huntington Disease Research.Metabolites · 2023Review
- Disease phenotype prediction in multiple sclerosis.iScience · 2023Article
- From biomedical cloud platforms to microservices: next steps in FAIR data and analysis.Scientific data · 2022Article
- Tackling the Challenges of 21Patterns (New York, N.Y.) · 2020Article
- Laniakea: an open solution to provide Galaxy "on-demand" instances over heterogeneous cloud infrastructures.GigaScience · 2020Article
- Targeted metabolomics of CSF in healthy individuals and patients with secondary progressive multiple sclerosis using high-resolution mass spectrometry.Metabolomics : Official journal of the Metabolomic Society · 2020Article
- FAIR digital objects in environmental and life sciences should comprise workflow operation design data and method information for repeatability of study setups and reproducibility of results.Database : the journal of biological databases and curation · 2020Article
- Experience in Developing an FHIR Medical Data Management Platform to Provide Clinical Decision Support.International journal of environmental research and public health · 2019Article
- PhenoMeNal: processing and analysis of metabolomics data in the cloud.GigaScience · 2019Article
- On-demand virtual research environments using microservices.PeerJ. Computer science · 2019Article
- Integration of magnetic resonance imaging and protein and metabolite CSF measurements to enable early diagnosis of secondary progressive multiple sclerosis.Theranostics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
35 authors.
Funding
Abstract
motivationDeveloping a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator.
resultsWe developed a Virtual Research Environment (VRE) which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science. AVAILABILITY AND IMPLEMENTATION: The PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the Virtual Research Environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Registered trials
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.