Demarcating good solutions in system biology computer models using artificial neural networks
How close a computer model comes to recreating real-world phenomena often depends on the value of its internal parameters, but investigating the outcome of the model for every point in parameter space is in practice an impossible task. Here an artificial neural network is used as a numerical predictor on two different system biology computer models. A semi-implicit solver was also implemented for
