Gene networks modeling of microarray time series using Fuzzy Granger causality

The life of living beings from cell to society in the universe is controlled by complex processes to preserve life. Understanding the gene network and discovering interactions between genes in cells is an important goal in biological systems. Modeling the gene network is one of the important issues in signal processing at the gene level. After the development of microarray technology, it was possible to model this network using time series data. The main objective of this research is to model the gene network from microarray time-series data that uses Granger causality, and to improve Granger causality and to observe the vague nature of microarray data,The linear method in Granger causality is replaced by a fuzzy method which then was applied on artificial and the real HELA data.