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PMID: 20851208 已发表 · ppublish 英语

Exposing the cancer genome atlas as a SPARQL endpoint.

Journal of biomedical informatics ·第 43 卷 ·第 6 期 ·2011-03-18

Deus(Helena F),Veiga(Diogo F),Freire(Pablo R),Weinstein(John N),Mills(Gordon B),Almeida(Jonas S)

摘要

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.

文献信息
期刊
Journal of biomedical informatics
期刊简称
J Biomed Inform
发表日期
2011-03-18
收录日期
2010-11-24
更新日期
2016-12-03
语言
英语
国家/地区
United States
NLM ID
100970413
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