Title :
An Agent-Based Hybrid System for Microarray Data Analysis
Author :
Zhang, Zili ; Yang, Pengyi ; Wu, Xindong ; Zhang, Chengqi
Author_Institution :
Southwest Univ., Chongqing, China
Abstract :
This article reports our experience in agent-based hybrid construction for microarray data analysis. The contributions are twofold: We demonstrate that agent-based approaches are suitable for building hybrid systems in general, and that a genetic ensemble system is appropriate for microarray data analysis in particular. Created using an agent-based framework, this genetic ensemble system for microarray data analysis excels in both sample classification accuracy and gene selection reproducibility.
Keywords :
biology computing; data analysis; genetic algorithms; genetics; learning (artificial intelligence); multi-agent systems; pattern classification; agent-based hybrid system; gene classification accuracy; gene selection reproducibility; genetic ensemble system; genetic-algorithm; microarray data analysis; multiagent system; Algorithm design and analysis; Australia; Bioinformatics; Data analysis; Genetic algorithms; Hybrid intelligent systems; Intelligent agent; Multiagent systems; Reproducibility of results; System testing; bioinformatics; data mining; hybrid systems; intelligent agents; microarray;
Journal_Title :
Intelligent Systems, IEEE
DOI :
10.1109/MIS.2009.92
