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Omicseq: a web-based search engine for exploring omics datasets
The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5793835/ https://www.ncbi.nlm.nih.gov/pubmed/28402462 http://dx.doi.org/10.1093/nar/gkx258 |
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author | Sun, Xiaobo Pittard, William S. Xu, Tianlei Chen, Li Zwick, Michael E. Jiang, Xiaoqian Wang, Fusheng Qin, Zhaohui S. |
author_facet | Sun, Xiaobo Pittard, William S. Xu, Tianlei Chen, Li Zwick, Michael E. Jiang, Xiaoqian Wang, Fusheng Qin, Zhaohui S. |
author_sort | Sun, Xiaobo |
collection | PubMed |
description | The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve ‘findability’ of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. |
format | Online Article Text |
id | pubmed-5793835 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57938352018-02-06 Omicseq: a web-based search engine for exploring omics datasets Sun, Xiaobo Pittard, William S. Xu, Tianlei Chen, Li Zwick, Michael E. Jiang, Xiaoqian Wang, Fusheng Qin, Zhaohui S. Nucleic Acids Res Web Server Issue The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve ‘findability’ of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org. Oxford University Press 2017-07-03 2017-04-10 /pmc/articles/PMC5793835/ /pubmed/28402462 http://dx.doi.org/10.1093/nar/gkx258 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Web Server Issue Sun, Xiaobo Pittard, William S. Xu, Tianlei Chen, Li Zwick, Michael E. Jiang, Xiaoqian Wang, Fusheng Qin, Zhaohui S. Omicseq: a web-based search engine for exploring omics datasets |
title | Omicseq: a web-based search engine for exploring omics datasets |
title_full | Omicseq: a web-based search engine for exploring omics datasets |
title_fullStr | Omicseq: a web-based search engine for exploring omics datasets |
title_full_unstemmed | Omicseq: a web-based search engine for exploring omics datasets |
title_short | Omicseq: a web-based search engine for exploring omics datasets |
title_sort | omicseq: a web-based search engine for exploring omics datasets |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5793835/ https://www.ncbi.nlm.nih.gov/pubmed/28402462 http://dx.doi.org/10.1093/nar/gkx258 |
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