Data Mining in Genomics and ProteomicsView this Special Issue
Research article | Open Access
Nadim W. Alkharouf, D. Curtis Jamison, Benjamin F. Matthews, "Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases", BioMed Research International, vol. 2005, Article ID 729240, 8 pages, 2005. https://doi.org/10.1155/JBB.2005.181
Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases
Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB.
Copyright © 2005 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.