Agent Technology for Data Analytics of Gene Expression Data: A Literature Review

Abstract

Analytics of gene expression data is the prolonged research area of present situation. Analysis of gene expression data requires enormous amount of work and huge set of algorithms. Using agent computing we deal with complex systems which are discovered many opportunities for developing data mining systems in a different ways. Hence to create predictive models, there is a huge need for intelligent and autonomous software agents which can procure useful information from the large datasets of raw information. Predictive analytics models can be created from these datasets which can be further used for various applications in security, future prediction etc. This research paper gives an overall function of multi agent systems in analytics of gene expression data, in terms of characteristics, adaptability, reliability and robotics of agents. Analytics on gene expression data is one of the emerging research fields. A large set of methodology and algorithms are existing in the field but in the application of agent technology in the field of gene expression data is at the infant stage. So the aim of this review paper is to integrate agent technology in the gene expression data analytics.