Abstract
BackgroundThe 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.ResultsGeneKeyDB 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.ConclusionGeneKeyDB can enable analysis tools and users to manipulate the intersections, unions, and differences among different data sets.
Highlights
The analysis of biological data is greatly enhanced by existing or emerging databases
We have developed GeneKeyDB, a relational database, in an attempt to address these issues
Converting between multiple database identifiers is still a challenge as there is no current method to uniquely identify the same gene across multiple databases
Summary
The analysis of biological data is greatly enhanced by existing or emerging databases. 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. APIs are needed for computers to process the sets of the genes and gene products that are found in these biological networks. Both computational tools and advanced data mining environments need to use these APIs to access and manipulate large,
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