SynthesisBMC medical genomics2009
A metadata approach for clinical data management in translational genomics studies in breast cancer.
Synthesis in BMC medical genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- From manual entry to machine precision: challenges and evolution of metadata schema development in collaborative research centers.BMC research notes · 2026Article
- The Impact of the Coexpression ofThe breast journal · 2024Article
- Article
- The Assisi Think Tank Meeting Breast Large Database for Standardized Data Collection in Breast Cancer-ATTM.BLADE.Journal of personalized medicine · 2021Article
- An ontology-based documentation of data discovery and integration process in cancer outcomes research.BMC medical informatics and decision making · 2020Article
- Common data elements of breast cancer for research databases: A systematic review.Journal of family medicine and primary care · 2020Review
- Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned.Briefings in bioinformatics · 2017Article
- Big Data: the challenge for small research groups in the era of cancer genomics.British journal of cancer · 2015Review
- Article
- Article
- Clinical Data Element Ontology for Unified Indexing and Retrieval of Data Elements across Multiple Metadata Registries.Healthcare informatics research · 2014Article
- A digital repository with an extensible data model for biobanking and genomic analysis management.BMC genomics · 2014Article
- Hadron therapy information sharing prototype.Journal of radiation research · 2013Article
- A metadata-aware application for remote scoring and exchange of tissue microarray images.BMC bioinformatics · 2013Article
- BeadDataPackR: A Tool to Facilitate the Sharing of Raw Data from Illumina BeadArray Studies.Cancer informatics · 2010Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
backgroundIn molecular profiling studies of cancer patients, experimental and clinical data are combined in order to understand the clinical heterogeneity of the disease: clinical information for each subject needs to be linked to tumour samples, macromolecules extracted, and experimental results. This may involve the integration of clinical data sets from several different sources: these data sets may employ different data definitions and some may be incomplete.
methodsIn this work we employ semantic web techniques developed within the CancerGrid project, in particular the use of metadata elements and logic-based inference to annotate heterogeneous clinical information, integrate and query it.
resultsWe show how this integration can be achieved automatically, following the declaration of appropriate metadata elements for each clinical data set; we demonstrate the practicality of this approach through application to experimental results and clinical data from five hospitals in the UK and Canada, undertaken as part of the METABRIC project (Molecular Taxonomy of Breast Cancer International Consortium).
conclusionWe describe a metadata approach for managing similarities and differences in clinical datasets in a standardized way that uses Common Data Elements (CDEs). We apply and evaluate the approach by integrating the five different clinical datasets of METABRIC.
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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.