Andrew J. Robinson
ABSTRACT
This paper presents a solution to the problem of creating a subset database from the public genome databases, also known as a database view. While the techniques to generate views are well established already in the database system there are still some problems found where applying this technique in the genome database environment. The main problems that exist in the current methods of view creation are missing relevant results, returning irrelevant results and view creation processes are generally very time consuming for the user. The solution presented within provides an automated approach aimed at reducing the time needed to create a view, which is usually done by hand. The solution improves the searching method needed for view creation by the addition of two extra phases; the first, expanding the keyword search so that it captures all relevant results and second, a filtering phase to remove all the extra irrelevant results. The whole process is done in the background so that the user isn't required to spend much time fixing the results of inadequate search tools.
- Andrew Robinson and Wenny Rahayu (2004) Genome database integration, ICCSA 2004, LNCS 3045, pp 443--453Google Scholar
Cross Ref
- Stephan Philippi (2004) Light-weight integration of molecular biological databases, Bioinformatics, pp 51--57. Google ScholarDigital Library
- Jacob Kohler, Stephan Philippi and Matthias Lange (2003) SEMEDA: ontology based semantic integration of biological databases, Bioinformatics, pp 2420--2427.Google Scholar
- http://www.cogsci.princeton.edu/~wn/, Wordnet, Princeton University, NJ.Google Scholar
- http://www.geneontology.org/, Gene Ontology Consortium, Gene Ontology Consortium.Google Scholar
- David Megginson, (1994) Hyper Grammar http://www.uottawa.ca/academic/arts/writcent/hypergrammar /grammar.html, University of Ottawa Canada.Google Scholar
- www.expasy.org/sprot/, ExPASy - Swiss-Prot and TrEMBL, Swiss Institute for Bioinformatics (SIB) and European Bioinformatics Institute (EBI).Google Scholar
- Natalya F. Noy and Deborah L. McGuinness (2001) Ontology Development 101: A Guide to Creating Your First Ontology, Stanford Report KSL-01-05 and SMI-2001-0880.Google Scholar
- Daniel Sleator and Davy Temperley (1993) Parsing English with a Link Grammar. Third International Workshop on Parsing TechnologiesGoogle Scholar
- T. K. Attwood, M. D. R. Croning, D. R. Flower, A. P. Lewis, J. E. Mabey, P. Scordis, J. N. Selly and W. Wright (2000) PRINTS-S the database formerly known as PRINTS, Nucleic Acids Research, pp. 225--227.Google ScholarCross Ref
- Yury V. Bukhman and Jeffrey Skolnick (2001) BioMolQuest: integrated database-based retrieval of protein structural and functional information, Bioinformatics Vol. 12 no. 5, pp. 468--478.Google ScholarCross Ref
Index Terms
- User-defined view automation of genomic databases
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