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Updated: Aug 9, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Microarray data mining using gene ontology
S Li1, M J Becich, J Gilbertson
1Center for Pathology Informatics, Department of Pathology, Benedum Oncology Informatics Center, University of Pittsburgh, Cancer Institute, University Pittsburgh, Medical School, 15232, USA. lis@msx.upmc.edu
Abstract:
DNA microarray technology allows scientists to study the expression of thousands of genes--potentially entire genomes--simultaneously. However the large number of genes, variety of statistical methods employed and the complexity of biologic systems complicate analysis of microarray results. We have developed a web based environment that simplifies the presentation of microarray results by combining microarray results processed for statistical significance with probe set annotation by Genbank, NCBI RefSeqs, GeneCards and the Gene Ontology. This allows rapid examination and classification of microarray experiments--annotated by NCIBI tools --by Statistical Significance and Gene Oncology Classes. By providing a simple, easily understood interface to large microarray data sets, this tool has been particularly useful for small research groups focused on a small number of related genes and for researchers who want to ask simple questions without the overhead of complex data management and analysis.
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