Multi-agent System for Gene Expression Analysis to Identify Involved Genes in Cervical Cancer

This paper presents an application of multi-agent systems for gene expression analysis, the agents use statistical methods, machine learning and genomical information from external data bases to identify involved genes in cervical cancer process. The multi-agent system for gene expression analysis from reading of oligonucleotide microarray is integrated by five operational agents in charge of the fundamental processes of the system, and a manager who organizes and coordinates the work of the system. The agent platform are separated from procedures of statistical methods and machine learning in order to give independence and flexibility to the system.