ArticleBMC bioinformatics2009
Ontology-driven indexing of public datasets for translational bioinformatics.
Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
What it found
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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.
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Who cites it
55 citing papers in PubMed.
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- Processing genome-wide association studies within a repository of heterogeneous genomic datasets.BMC genomic data · 2023Article
- Systematic tissue annotations of genomics samples by modeling unstructured metadata.Nature communications · 2022Article
- Bias-invariant RNA-sequencing metadata annotation.GigaScience · 2021Article
- ACE: the Advanced Cohort Engine for searching longitudinal patient records.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Use of the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) for Processing Free Text in Health Care: Systematic Scoping Review.Journal of medical Internet research · 2021Article
- Artificial Intelligence Pipeline to Bridge the Gap between Bench Researchers and Clinical Researchers in Precision Medicine.Med one · 2020Article
- Enhancing Clinical Data and Clinical Research Data with Biomedical Ontologies - Insights from the Knowledge Representation Perspective.Yearbook of medical informatics · 2019Article
- SIFR annotator: ontology-based semantic annotation of French biomedical text and clinical notes.BMC bioinformatics · 2018Article
- DataMed - an open source discovery index for finding biomedical datasets.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Finding relevant biomedical datasets: the UC San Diego solution for the bioCADDIE Retrieval Challenge.Database : the journal of biological databases and curation · 2018Article
- Vitamin D Receptor Signaling and Cancer.Endocrinology and metabolism clinics of North America · 2017Review
- MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive.Bioinformatics (Oxford, England) · 2017Article
- A publicly available benchmark for biomedical dataset retrieval: the reference standard for the 2016 bioCADDIE dataset retrieval challenge.Database : the journal of biological databases and curation · 2017Article
- Synthesizer: Expediting synthesis studies from context-free data with information retrieval techniques.PloS one · 2017Article
- Genomic insights into ayurvedic and western approaches to personalized medicine.Journal of genetics · 2016Review
- Assessing Metadata Quality of a Federally Sponsored Health Data Repository.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2016Article
- Using LASSO Regression to Predict Rheumatoid Arthritis Treatment Efficacy.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2016Article
- Vitamin D receptor and RXR in the post-genomic era.Journal of cellular physiology · 2015Review
- Surveillance for the prevention of chronic diseases through information association.BMC medical genomics · 2014Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The volume of publicly available genomic scale data is increasing. Genomic datasets in public repositories are annotated with free-text fields describing the pathological state of the studied sample. These annotations are not mapped to concepts in any ontology, making it difficult to integrate these datasets across repositories. We have previously developed methods to map text-annotations of tissue microarrays to concepts in the NCI thesaurus and SNOMED-CT. In this work we generalize our methods to map text annotations of gene expression datasets to concepts in the UMLS. We demonstrate the utility of our methods by processing annotations of datasets in the Gene Expression Omnibus. We demonstrate that we enable ontology-based querying and integration of tissue and gene expression microarray data. We enable identification of datasets on specific diseases across both repositories. Our approach provides the basis for ontology-driven data integration for translational research on gene and protein expression data. Based on this work we have built a prototype system for ontology based annotation and indexing of biomedical data. The system processes the text metadata of diverse resource elements such as gene expression data sets, descriptions of radiology images, clinical-trial reports, and PubMed article abstracts to annotate and index them with concepts from appropriate ontologies. The key functionality of this system is to enable users to locate biomedical data resources related to particular ontology concepts.
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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.