System Modeling of Cell Survival and Cell Death : a Deterministic Model Using Fuzzy System

The extraction of some effective features that can represent the identities of different classes plays a critical factor for any classification problems involving the analysis of complex data. Fuzzy systems are an alternative to traditional notions of set membership and logic that has its origins in ancient Greek philosophy, and applications at the leading edge of Artificial Intelligence. Yet, despite its long-standing origins, it is a relatively new field, and as such leaves much room for development. In this paper we apply a fuzzy logic to the analysis of a large, systematic dataset describing the dynamics of cell signaling downstream of TNF, EGF and Insulin receptors regulating cell survival and cell death. Simulations based on fuzzy logic recapitulate most features of the data and generate several predictions involving pathway crosstalk and regulation. The system modeling for cell survival and cell death has been implemented using Fuzzy Logic Toolbox software with MATLAB which is technical computing software as a tool for solving problems. The results obtain will give information on how the input signals inducing cell survival/death should be modulated to achieve desire outputs and thus helps the experimentalists to design proposals regarding possible improvements to cell survival/ cell death.