Design of Computational Grid-based Intelligence ART1 Classification System for Bioinformatics Applications

Computational grid technology has been noticed as an issue to solve large-scale bioinformatics-related problems and improves data accuracy and processing speed on multiple computation platforms with distributed bioDATA sets. This paper proposes a grid-based intelligence ART1 classifier which operates an ART1 clustering classification using grid computational resources with distributed GPCR data sets. This paper evaluates performance of the grid-based ART1 classifier in comparing to the grid-based ART1 classifier and the grid-based 3-tier ART1 classifier. The number of communication message of the grid-based intelligence ART1 classifier is less than the others classifier. And the classification processing time of the grid-based intelligence ART1 classifier is 13% classification processing time of the grid-based ART1 classifier and is 25% classification processing time of the grid-based 3-tier ART1 classifier. Computational grid in bioinformatics applications gives a great promise of high performance processing with large-scale and geographically distributed bioDATA sets and provides a good progress in guaranteeing high bioData accuracy with reasonable processing resources