ArticleJournal of biomedical informatics2010
Exposing the cancer genome atlas as a SPARQL endpoint.
Article in Journal of biomedical informatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
13 citing papers in PubMed.
- Ontology-Enhanced Representations of Non-image Data in The Cancer Imaging Archive.CEUR workshop proceedings · 2018Article
- Article
- kpath: integration of metabolic pathway linked data.Database : the journal of biological databases and curation · 2015Article
- QMachine: commodity supercomputing in web browsers.BMC bioinformatics · 2014Article
- Non-synonymous variations in cancer and their effects on the human proteome: workflow for NGS data biocuration and proteome-wide analysis of TCGA data.BMC bioinformatics · 2014Article
- TopFed: TCGA tailored federated query processing and linking to LOD.Journal of biomedical semantics · 2014Article
- Next generation distributed computing for cancer research.Cancer informatics · 2014Review
- MicroRNA 4423 is a primate-specific regulator of airway epithelial cell differentiation and lung carcinogenesis.Proceedings of the National Academy of Sciences of the United States of America · 2013Article
- A self-updating road map of The Cancer Genome Atlas.Bioinformatics (Oxford, England) · 2013Article
- The Third ACGG-DB Meeting Report: Towards an international collaborative infrastructure for glycobioinformatics.Glycobiology · 2013Article
- S3QL: a distributed domain specific language for controlled semantic integration of life sciences data.BMC bioinformatics · 2011Article
- Integration and analysis of genome-scale data from gliomas.Nature reviews. Neurology · 2011Review
- AGUIA: autonomous graphical user interface assembly for clinical trials semantic data services.BMC medical informatics and decision making · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The Cancer Genome Atlas (TCGA) is a multidisciplinary, multi-institutional effort to characterize several types of cancer. Datasets from biomedical domains such as TCGA present a particularly challenging task for those interested in dynamically aggregating its results because the data sources are typically both heterogeneous and distributed. The Linked Data best practices offer a solution to integrate and discover data with those characteristics, namely through exposure of data as Web services supporting SPARQL, the Resource Description Framework query language. Most SPARQL endpoints, however, cannot easily be queried by data experts. Furthermore, exposing experimental data as SPARQL endpoints remains a challenging task because, in most cases, data must first be converted to Resource Description Framework triples. In line with those requirements, we have developed an infrastructure to expose clinical, demographic and molecular data elements generated by TCGA as a SPARQL endpoint by assigning elements to entities of the Simple Sloppy Semantic Database (S3DB) management model. All components of the infrastructure are available as independent Representational State Transfer (REST) Web services to encourage reusability, and a simple interface was developed to automatically assemble SPARQL queries by navigating a representation of the TCGA domain. A key feature of the proposed solution that greatly facilitates assembly of SPARQL queries is the distinction between the TCGA domain descriptors and data elements. Furthermore, the use of the S3DB management model as a mediator enables queries to both public and protected data without the need for prior submission to a single data source.
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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.