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Relax with CouchDB - Into the non-relational DBMS era of bioinformatics

  • Ganiraju Manyam
    ,
  • Michelle A. Payton
    ,
  • Jack A. Roth
    ,
  • Lynne V. Abruzzo
    ,
  • Kevin R. Coombes(corresponding author)
*Corresponding author for this work
  • University of Texas MD Anderson Cancer Center
Scholary Output:
Contribution to journal
Article
Peer-review

Open access

Abstract

With the proliferation of high-throughput technologies, genome-level data analysis has become common in molecular biology. Bioinformaticians are developing extensive resources to annotate and mine biological features from high-throughput data. The underlying database management systems for most bioinformatics software are based on a relational model. Modern non-relational databases offer an alternative that has flexibility, scalability, and a non-rigid design schema. Moreover, with an accelerated development pace, non-relational databases like CouchDB can be ideal tools to construct bioinformatics utilities. We describe CouchDB by presenting three new bioinformatics resources: (a) geneSmash, which collates data from bioinformatics resources and provides automated gene-centric annotations, (b) drugBase, a database of drug-target interactions with a web interface powered by geneSmash, and (c) HapMap-CN, which provides a web interface to query copy number variations from three SNP-chip HapMap datasets. In addition to the web sites, all three systems can be accessed programmatically via web services.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 1-7 (7 pages)

Journal (Volume, Issue Number)

Genomics (Volume 100, Issue 1)

Publication milestones

  • Published - 07/2012

Publication status

Published - 07/2012

ISSN

0888-7543

Publication IDs

  • Scopus: 84862753629
  • PubMed: 22609849

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Scopus
citations
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1
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0.20
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4
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0.80
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1
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1

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Funding Details

This work was supported in part by grants R01 CA123252 , P30 CA016672 , and P50 CA070907 from the National Cancer Institute of the National Institutes of Health .
FundersFunding number
NIH
-
NCI
P30CA016672