Probability-based ART1 Clustering Classification for Bioinformatics Application in Computational Grid

Bioinformatics is an innovative research field of science, which applies power of high performance system using computational grid technology. This paper focuses on a bioinformatics data classification and data accuracy problem which is currently important issue in bioinformatics applications. This paper proposes a probability-based ART1 clustering classification model. The recognition success rates of ART1 clustering classificaton with PNN verification are over 95%. PNN verification filters inadequate data of ART1 clusters and improves data accuracy of ART1 class clusters.