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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Main Authors: Zhang B, Schmoyer D, Baker E, Peng X, Kirov SA, Snoddy J
Format: Article
Language:English
Published: BMC 2005-03-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/6/72
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spelling 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
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