%0 Journal Article
%T Using Semantic Web Technologies to Enable Cancer Genomics Discovery
at Petabyte Scale
%A Adam Stanojevic
%A Brandi Davis-Dusenbery
%A Deniz Kural
%A Dragan Bajcic
%A Dragan Djordjevic
%A Filip Jelic
%A Jelena Radenkovic
%A Jessica Lau
%A Jovan Cejovic
%A Milica Miletic
%A Milos Nesic
%A Nick Groves-Kirkby
%A Patrick Grady
%A Stevan Radanovic
%A Vladimir Mladenovic
%J Archive of "Cancer Informatics".
%D 2018
%R 10.1177/1176935118774787
%X 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¨Cbased 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
%K TCGA
%K cancer
%K genomics
%K cloud
%K Semantic Web
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6166304/