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BioWarehouse: a bioinformatics database warehouse toolkit.

Publication ,  Journal Article
Lee, TJ; Pouliot, Y; Wagner, V; Gupta, P; Stringer-Calvert, DWJ; Tenenbaum, JD; Karp, PD
Published in: BMC Bioinformatics
March 23, 2006

BACKGROUND: This article addresses the problem of interoperation of heterogeneous bioinformatics databases. RESULTS: We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. CONCLUSION: BioWarehouse embodies significant progress on the database integration problem for bioinformatics.

Duke Scholars

Published In

BMC Bioinformatics

DOI

EISSN

1471-2105

Publication Date

March 23, 2006

Volume

7

Start / End Page

170

Location

England

Related Subject Headings

  • Software
  • Signal Transduction
  • Semantics
  • Proteins
  • Protein Engineering
  • Databases, Protein
  • Databases, Genetic
  • Databases, Factual
  • Database Management Systems
  • Computational Biology
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Lee, T. J., Pouliot, Y., Wagner, V., Gupta, P., Stringer-Calvert, D. W. J., Tenenbaum, J. D., & Karp, P. D. (2006). BioWarehouse: a bioinformatics database warehouse toolkit. BMC Bioinformatics, 7, 170. https://doi.org/10.1186/1471-2105-7-170
Lee, Thomas J., Yannick Pouliot, Valerie Wagner, Priyanka Gupta, David W. J. Stringer-Calvert, Jessica D. Tenenbaum, and Peter D. Karp. “BioWarehouse: a bioinformatics database warehouse toolkit.BMC Bioinformatics 7 (March 23, 2006): 170. https://doi.org/10.1186/1471-2105-7-170.
Lee TJ, Pouliot Y, Wagner V, Gupta P, Stringer-Calvert DWJ, Tenenbaum JD, et al. BioWarehouse: a bioinformatics database warehouse toolkit. BMC Bioinformatics. 2006 Mar 23;7:170.
Lee, Thomas J., et al. “BioWarehouse: a bioinformatics database warehouse toolkit.BMC Bioinformatics, vol. 7, Mar. 2006, p. 170. Pubmed, doi:10.1186/1471-2105-7-170.
Lee TJ, Pouliot Y, Wagner V, Gupta P, Stringer-Calvert DWJ, Tenenbaum JD, Karp PD. BioWarehouse: a bioinformatics database warehouse toolkit. BMC Bioinformatics. 2006 Mar 23;7:170.
Journal cover image

Published In

BMC Bioinformatics

DOI

EISSN

1471-2105

Publication Date

March 23, 2006

Volume

7

Start / End Page

170

Location

England

Related Subject Headings

  • Software
  • Signal Transduction
  • Semantics
  • Proteins
  • Protein Engineering
  • Databases, Protein
  • Databases, Genetic
  • Databases, Factual
  • Database Management Systems
  • Computational Biology