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Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale
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 respons...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6166304/ https://www.ncbi.nlm.nih.gov/pubmed/30283230 http://dx.doi.org/10.1177/1176935118774787 |
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author | Cejovic, Jovan Radenkovic, Jelena Mladenovic, Vladimir Stanojevic, Adam Miletic, Milica Radanovic, Stevan Bajcic, Dragan Djordjevic, Dragan Jelic, Filip Nesic, Milos Lau, Jessica Grady, Patrick Groves-Kirkby, Nick Kural, Deniz Davis-Dusenbery, Brandi |
author_facet | Cejovic, Jovan Radenkovic, Jelena Mladenovic, Vladimir Stanojevic, Adam Miletic, Milica Radanovic, Stevan Bajcic, Dragan Djordjevic, Dragan Jelic, Filip Nesic, Milos Lau, Jessica Grady, Patrick Groves-Kirkby, Nick Kural, Deniz Davis-Dusenbery, Brandi |
author_sort | Cejovic, Jovan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6166304 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-61663042018-10-03 Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale Cejovic, Jovan Radenkovic, Jelena Mladenovic, Vladimir Stanojevic, Adam Miletic, Milica Radanovic, Stevan Bajcic, Dragan Djordjevic, Dragan Jelic, Filip Nesic, Milos Lau, Jessica Grady, Patrick Groves-Kirkby, Nick Kural, Deniz Davis-Dusenbery, Brandi Cancer Inform Sequencing for the Masses: Another Desktop Revolution - Review 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. SAGE Publications 2018-09-28 /pmc/articles/PMC6166304/ /pubmed/30283230 http://dx.doi.org/10.1177/1176935118774787 Text en © The Author(s) 2018 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Sequencing for the Masses: Another Desktop Revolution - Review Cejovic, Jovan Radenkovic, Jelena Mladenovic, Vladimir Stanojevic, Adam Miletic, Milica Radanovic, Stevan Bajcic, Dragan Djordjevic, Dragan Jelic, Filip Nesic, Milos Lau, Jessica Grady, Patrick Groves-Kirkby, Nick Kural, Deniz Davis-Dusenbery, Brandi Using Semantic Web Technologies to Enable Cancer Genomics Discovery at Petabyte Scale |
title | Using Semantic Web Technologies to Enable Cancer Genomics Discovery
at Petabyte Scale |
title_full | Using Semantic Web Technologies to Enable Cancer Genomics Discovery
at Petabyte Scale |
title_fullStr | Using Semantic Web Technologies to Enable Cancer Genomics Discovery
at Petabyte Scale |
title_full_unstemmed | Using Semantic Web Technologies to Enable Cancer Genomics Discovery
at Petabyte Scale |
title_short | Using Semantic Web Technologies to Enable Cancer Genomics Discovery
at Petabyte Scale |
title_sort | using semantic web technologies to enable cancer genomics discovery
at petabyte scale |
topic | Sequencing for the Masses: Another Desktop Revolution - Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6166304/ https://www.ncbi.nlm.nih.gov/pubmed/30283230 http://dx.doi.org/10.1177/1176935118774787 |
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