24th Annual International Conference of the Engineering-in-Medicine-and-Biology-Society/Annual Fall Meeting of the Biomedical-Engineering-Society (EMBS 2002 BMES), Texas, United States Of America, 23 - 26 October 2002, pp.2184-2185, (Full Text)
In this paper, the radial basis function (RBF) network method with the Mahalanobis distance was applied to predict the content of protein secondary structure elements. A study of the Mahalanobis-RBF with different window sizes on the dataset developed by Qian-Sejnowski is given. The RBF network predicts each position in turn based on a local window of residues, by sliding this window along the length of the sequence. Comparison of Gaussian-RBF and Mahalanobis-RBF on the Qian dataset shows that the Mahalanobis distance in using RBF gives better results in the prediction of secondary structure for local sequence structural state.