Literature DB >> 15564301

Constructing ontology-driven protein family databases.

K Wolstencroft1, R McEntire, R Stevens, L Tabernero, A Brass.   

Abstract

MOTIVATION: Protein family databases provide a central focus for scientific communities as well as providing useful resources to aide research. However, such resources require constant curation and often become outdated and discontinued. We have developed an ontology-driven system for capturing and managing protein family data that addresses the problems of maintenance and sustainability.
RESULTS: Using protein phosphatases and ABC transporters as model protein families, we constructed two protein family database resources around a central DAML+OIL ontology. Each resource contains specialist information about each protein family, providing specialized domain-specific resources based on the same template structure. The formal structure, combined with the extraction of biological data using GO terms, allows for automated update strategies. Despite the functional differences between the two protein families, the ontology model was equally applicable to both, demonstrating the generic nature of the system. AVAILABILITY: The protein phosphatase resource, PhosphaBase, is freely available on the internet (http://www.bioinf.man.ac.uk/phosphabase). The DAML+OIL ontology for the protein phosphatases and the ABC transporters is available on request from the authors. CONTACT: kwolstencroft@cs.man.ac.uk.

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Year:  2004        PMID: 15564301     DOI: 10.1093/bioinformatics/bti158

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

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Journal:  PLoS One       Date:  2011-12-14       Impact factor: 3.240

2.  INVHOGEN: a database of homologous invertebrate genes.

Authors:  Ingo Paulsen; Arndt von Haeseler
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

3.  MAO: a Multiple Alignment Ontology for nucleic acid and protein sequences.

Authors:  Julie D Thompson; Stephen R Holbrook; Kazutaka Katoh; Patrice Koehl; Dino Moras; Eric Westhof; Olivier Poch
Journal:  Nucleic Acids Res       Date:  2005-07-25       Impact factor: 16.971

4.  Ontologies for bioinformatics.

Authors:  Nadine Schuurman; Agnieszka Leszczynski
Journal:  Bioinform Biol Insights       Date:  2008-03-12

5.  OPPL-Galaxy, a Galaxy tool for enhancing ontology exploitation as part of bioinformatics workflows.

Authors:  Mikel Egaña Aranguren; Jesualdo Tomás Fernández-Breis; Chris Mungall; Erick Antezana; Alejandro Rodríguez González; Mark D Wilkinson
Journal:  J Biomed Semantics       Date:  2013-01-04
  5 in total

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