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BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery
Single-nucleotide variation and gene expression of disease samples represent important resources for biomarker discovery. Many databases have been built to host and make available such data to the community, but these databases are frequently limited in scope and/or content. BioMuta, a database of c...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753215/ https://www.ncbi.nlm.nih.gov/pubmed/30053270 http://dx.doi.org/10.1093/nar/gkx907 |
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author | Dingerdissen, Hayley M Torcivia-Rodriguez, John Hu, Yu Chang, Ting-Chia Mazumder, Raja Kahsay, Robel |
author_facet | Dingerdissen, Hayley M Torcivia-Rodriguez, John Hu, Yu Chang, Ting-Chia Mazumder, Raja Kahsay, Robel |
author_sort | Dingerdissen, Hayley M |
collection | PubMed |
description | Single-nucleotide variation and gene expression of disease samples represent important resources for biomarker discovery. Many databases have been built to host and make available such data to the community, but these databases are frequently limited in scope and/or content. BioMuta, a database of cancer-associated single-nucleotide variations, and BioXpress, a database of cancer-associated differentially expressed genes and microRNAs, differ from other disease-associated variation and expression databases primarily through the aggregation of data across many studies into a single source with a unified representation and annotation of functional attributes. Early versions of these resources were initiated by pilot funding for specific research applications, but newly awarded funds have enabled hardening of these databases to production-level quality and will allow for sustained development of these resources for the next few years. Because both resources were developed using a similar methodology of integration, curation, unification, and annotation, we present BioMuta and BioXpress as allied databases that will facilitate a more comprehensive view of gene associations in cancer. BioMuta and BioXpress are hosted on the High-performance Integrated Virtual Environment (HIVE) server at the George Washington University at https://hive.biochemistry.gwu.edu/biomuta and https://hive.biochemistry.gwu.edu/bioxpress, respectively. |
format | Online Article Text |
id | pubmed-5753215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-57532152018-01-05 BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery Dingerdissen, Hayley M Torcivia-Rodriguez, John Hu, Yu Chang, Ting-Chia Mazumder, Raja Kahsay, Robel Nucleic Acids Res Database Issue Single-nucleotide variation and gene expression of disease samples represent important resources for biomarker discovery. Many databases have been built to host and make available such data to the community, but these databases are frequently limited in scope and/or content. BioMuta, a database of cancer-associated single-nucleotide variations, and BioXpress, a database of cancer-associated differentially expressed genes and microRNAs, differ from other disease-associated variation and expression databases primarily through the aggregation of data across many studies into a single source with a unified representation and annotation of functional attributes. Early versions of these resources were initiated by pilot funding for specific research applications, but newly awarded funds have enabled hardening of these databases to production-level quality and will allow for sustained development of these resources for the next few years. Because both resources were developed using a similar methodology of integration, curation, unification, and annotation, we present BioMuta and BioXpress as allied databases that will facilitate a more comprehensive view of gene associations in cancer. BioMuta and BioXpress are hosted on the High-performance Integrated Virtual Environment (HIVE) server at the George Washington University at https://hive.biochemistry.gwu.edu/biomuta and https://hive.biochemistry.gwu.edu/bioxpress, respectively. Oxford University Press 2018-01-04 2017-10-09 /pmc/articles/PMC5753215/ /pubmed/30053270 http://dx.doi.org/10.1093/nar/gkx907 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 | Database Issue Dingerdissen, Hayley M Torcivia-Rodriguez, John Hu, Yu Chang, Ting-Chia Mazumder, Raja Kahsay, Robel BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery |
title | BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery |
title_full | BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery |
title_fullStr | BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery |
title_full_unstemmed | BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery |
title_short | BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery |
title_sort | biomuta and bioxpress: mutation and expression knowledgebases for cancer biomarker discovery |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5753215/ https://www.ncbi.nlm.nih.gov/pubmed/30053270 http://dx.doi.org/10.1093/nar/gkx907 |
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