ReviewBriefings in bioinformatics2020
Implementing the FAIR Data Principles in precision oncology: review of supporting initiatives.
Review in Briefings in bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software.Metabolomics : Official journal of the Metabolomic Society · 2023Pooled it
- Model Context Protocol: The unexpected catalyst of a bioinformatics interoperability revolution.PLoS computational biology · 2026Article
- Artificial Intelligence in Transcriptomics: From Human-in-the-Loop to Agentic AI.Journal of personalized medicine · 2026Review
- AI-driven radiogenomics in gynecologic oncology: from radiological digital biopsy to a new paradigm in precision therapy.Frontiers in oncology · 2026Review
- Publicly available imaging datasets for age-related macular degeneration: Evaluation according to the Findable, Accessible, Interoperable, Reusable (FAIR) principles.Experimental eye research · 2025Review
- Fast Healthcare Interoperability Resources (FHIR)-Based Interoperability Design in Indonesia: Content Analysis of Developer Hub's Social Networking Service.JMIR formative research · 2025Article
- Semantic enrichment of Pomeranian health study data using LOINC and WHO-FIC terminology mapping principles.JAMIA open · 2025Article
- Leveraging Administrative Health Databases to Address Health Challenges in Farming Populations: Scoping Review and Bibliometric Analysis (1975-2024).JMIR public health and surveillance · 2025Article
- Datagraphy: toward a systematic approach to dataset discovery.GigaScience · 2025Article
- New implementation of data standards for AI in oncology: Experience from the EuCanImage project.GigaScience · 2025Article
- Large language models in oncology: a review.BMJ oncology · 2025Review
- Applying Findable, Accessible, Interoperable, and Reusable Principles to Biospecimens and Biobanks.Biopreservation and biobanking · 2024Article
- Establishing a Collaborative Genomic Repository for Adult Burn Survivors: A Burn Model System Feasibility Study.European burn journal · 2024Article
- Adapting the open-source Gen3 platform and kubernetes for the NIH HEAL IMPOWR and MIRHIQL clinical trial data commons: Customization, cloud transition, and optimization.Journal of biomedical informatics · 2024Article
- Building Flexible, Scalable, and Machine Learning-Ready Multimodal Oncology Datasets.Sensors (Basel, Switzerland) · 2024Article
- Standardizing digital biobanks: integrating imaging, genomic, and clinical data for precision medicine.Journal of translational medicine · 2024Review
- Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma: A quantitative review with Radiomics Quality Score.World journal of gastroenterology · 2024Review
- A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions.Frontiers in microbiology · 2024Review
- Current state of data stewardship tools in life science.Frontiers in big data · 2024Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Compelling research has recently shown that cancer is so heterogeneous that single research centres cannot produce enough data to fit prognostic and predictive models of sufficient accuracy. Data sharing in precision oncology is therefore of utmost importance. The Findable, Accessible, Interoperable and Reusable (FAIR) Data Principles have been developed to define good practices in data sharing. Motivated by the ambition of applying the FAIR Data Principles to our own clinical precision oncology implementations and research, we have performed a systematic literature review of potentially relevant initiatives. For clinical data, we suggest using the Genomic Data Commons model as a reference as it provides a field-tested and well-documented solution. Regarding classification of diagnosis, morphology and topography and drugs, we chose to follow the World Health Organization standards, i.e. ICD10, ICD-O-3 and Anatomical Therapeutic Chemical classifications, respectively. For the bioinformatics pipeline, the Genome Analysis ToolKit Best Practices using Docker containers offer a coherent solution and have therefore been selected. Regarding the naming of variants, we follow the Human Genome Variation Society's standard. For the IT infrastructure, we have built a centralized solution to participate in data sharing through federated solutions such as the Beacon Networks.
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What OpenQuestion holds
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.