Dear list members. I am trying to make a sensitivity analysis (as derived by Zurada 1994, Engelbrecht 1995) of input parameters (gene expression data) when applying a neural network to classify different cancer subtypes. Since I am no expert in the field, (rather a newbie), I wonder if there exists an implementation in R that can be used to measure the relative importance of the input variables for the neural network. The created network has (after PCA dimension reduction) 8 inputs, 2 nodes in the hidden layer and two outputs. I read somewhere that the sensitivity matrix is calculated by using a Jacobian matrix of the output parameters over the input parameters. I think that somehow I can grasp the concept, I just don?t know how to implement it in R. Any help, or guidelines would be greatly appreciated. Best regards Marcus