GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments
<p>Abstract</p> <p>Background</p> <p>The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support large scale computational analysis, but rather offer exclusively a...
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doaj-b3455bedfe174743b263fd0f16cb9a892020-11-25T01:55:00ZengBMCBMC Bioinformatics1471-21052005-03-01617210.1186/1471-2105-6-72GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environmentsZhang BSchmoyer DBaker EPeng XKirov SASnoddy J<p>Abstract</p> <p>Background</p> <p>The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support large scale computational analysis, but rather offer exclusively a web interface to the resource. We have recognized the growing need for a database which can be used successfully as a backend to computational analysis tools and pipelines. Such database should be sufficiently versatile to allow easy system integration.</p> <p>Results</p> <p>GeneKeyDB is a gene-centered relational database developed to enhance data mining in biological data sets. The system provides an underlying data layer for computational analysis tools and visualization tools. GeneKeyDB relies primarily on existing database identifiers derived from community databases (NCBI, GO, Ensembl, et al.) as well as the known relationships among those identifiers. It is a lightweight, portable, and extensible platform for integration with computational tools and analysis environments.</p> <p>Conclusion</p> <p>GeneKeyDB can enable analysis tools and users to manipulate the intersections, unions, and differences among different data sets.</p> http://www.biomedcentral.com/1471-2105/6/72 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhang B Schmoyer D Baker E Peng X Kirov SA Snoddy J |
spellingShingle |
Zhang B Schmoyer D Baker E Peng X Kirov SA Snoddy J GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments BMC Bioinformatics |
author_facet |
Zhang B Schmoyer D Baker E Peng X Kirov SA Snoddy J |
author_sort |
Zhang B |
title |
GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments |
title_short |
GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments |
title_full |
GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments |
title_fullStr |
GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments |
title_full_unstemmed |
GeneKeyDB: A lightweight, gene-centric, relational database to support data mining environments |
title_sort |
genekeydb: a lightweight, gene-centric, relational database to support data mining environments |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2005-03-01 |
description |
<p>Abstract</p> <p>Background</p> <p>The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support large scale computational analysis, but rather offer exclusively a web interface to the resource. We have recognized the growing need for a database which can be used successfully as a backend to computational analysis tools and pipelines. Such database should be sufficiently versatile to allow easy system integration.</p> <p>Results</p> <p>GeneKeyDB is a gene-centered relational database developed to enhance data mining in biological data sets. The system provides an underlying data layer for computational analysis tools and visualization tools. GeneKeyDB relies primarily on existing database identifiers derived from community databases (NCBI, GO, Ensembl, et al.) as well as the known relationships among those identifiers. It is a lightweight, portable, and extensible platform for integration with computational tools and analysis environments.</p> <p>Conclusion</p> <p>GeneKeyDB can enable analysis tools and users to manipulate the intersections, unions, and differences among different data sets.</p> |
url |
http://www.biomedcentral.com/1471-2105/6/72 |
work_keys_str_mv |
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