Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale
Autor: | Adam Stanojevic, Deniz Kural, Jessica W. Lau, Dragan Djordjevic, Jovan Cejovic, Milica Miletic, Brandi N. Davis-Dusenbery, Dragan Bajcic, Nick Groves-Kirkby, Vladimir Mladenović, Milos Nesic, Filip Jelic, Jelena Radenkovic, Patrick Grady, Stevan Radanovic |
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Rok vydání: | 2017 |
Předmět: |
0301 basic medicine
Cancer Research Computer science Process (engineering) 0206 medical engineering Cloud computing Genomics Sequencing for the Masses: Another Desktop Revolution - Review 02 engineering and technology USable lcsh:RC254-282 World Wide Web 03 medical and health sciences genomics cancer cloud Semantic Web business.industry Scale (chemistry) Petabyte TCGA lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens Data set 030104 developmental biology Oncology business 020602 bioinformatics |
Zdroj: | Cancer Informatics Cancer Informatics, Vol 17 (2018) |
ISSN: | 1176-9351 |
Popis: | Increased efforts in cancer genomics research and bioinformatics are producing tremendous amounts of data. These data are diverse in origin, format, and content. As the amount of available sequencing data increase, technologies that make them discoverable and usable are critically needed. In response, we have developed a Semantic Web–based Data Browser, a tool allowing users to visually build and execute ontology-driven queries. This approach simplifies access to available data and improves the process of using them in analyses on the Seven Bridges Cancer Genomics Cloud (CGC; www.cancergenomicscloud.org ). The Data Browser makes large data sets easily explorable and simplifies the retrieval of specific data of interest. Although initially implemented on top of The Cancer Genome Atlas (TCGA) data set, the Data Browser’s architecture allows for seamless integration of other data sets. By deploying it on the CGC, we have enabled remote researchers to access data and perform collaborative investigations. |
Databáze: | OpenAIRE |
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