ADAPTIVE NEURAL FUZZY INFERENCE SYSTEM FOR PREDICTING PROTEIN ACTIVITIES

Organism species activities can be exposed by protein concentration level. These activities produce nonlinear and complex behavior, therefore, Mathematical and computational modelling methods are becoming significant tool to elucidate this complex behavior. Moreover, these methods can be utilized to compute, predict and uncover the veiled knowledge. Unfortunately, most of the aforementioned approaches face the scarcity and the ambiguously in the biological knowledge to figure and expect protein concentrations measurements. Consequently, the purpose of this research introduces a computational model has the ability to work with vague and missing biological knowledge we derived a fuzzy logic model which predict protein concentrations; this research presented a new adaptive neural fuzzy inference system for predict protein concentration measurements level and exposes the nonlinear and the complex behavior for protein. The concern research utilize both fuzzy inference systems and artificial neural network which is identified as neuro fuzzy technique for elucidate the problem of predicting organism proteins concentration levels.