EM algorithms for PCA and SPCA
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Multivariate Data Reduction and Discrimination with SAS Software
Multivariate Data Reduction and Discrimination with SAS Software
Combining Few Neural Networks for Effective Secondary Structure Prediction
BIBE '03 Proceedings of the 3rd IEEE Symposium on BioInformatics and BioEngineering
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This paper presents the use of neural networks for the prediction of protein Secondary Structure. We propose a pre-processing stage based on the method of Cascaded Nonlinear Components Analysis (CNLPCA), in order to get a dimensional reduction of the data which may consider its nonlinearity. Then, the reduced data are placed in predictor networks and its results are combined. For the verification of possible improvements brought by the use of C-NLPCA, a set of tests was done and the results will be demonstrated in this paper. The C-NLPCA revealed to be efficient, propelling a new field of research.