Neural network based prediction technique for biological membrane studies

Neural networks are emerging as an important modeling tool for developing models of biological processes because of their inherent ability to represent nonlinear dynamics. In this work, a neural network model is attempted for the interaction of the surfactants with the red blood cell. The model predicts the dynamics of lysis fairly well for lysis above the 50% level, and the lysis can be specified. It is concluded that neural net models can save a lot of time, money and energy involved in repeating the same experiment with different cell numbers.