Omar Dario Urrego Cardenas - Academia.edu (original) (raw)
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Papers by Omar Dario Urrego Cardenas
A two-stage neural network has been used to predict protein secondary structure based on the posi... more A two-stage neural network has been used to predict protein secondary structure based on the position speci®c scoring matrices generated by PSI-BLAST. Despite the simplicity and convenience of the approach used, the results are found to be superior to those produced by other methods, including the popular PHD method according to our own benchmarking results and the results from the recent Critical Assessment of Techniques for Protein Structure Prediction experiment (CASP3), where the method was evaluated by stringent blind testing. Using a new testing set based on a set of 187 unique folds, and three-way cross-validation based on structural similarity criteria rather than sequence similarity criteria used previously (no similar folds were present in both the testing and training sets) the method presented here (PSIPRED) achieved an average Q 3 score of between 76.5 % to 78.3 % depending on the precise de®nition of observed secondary structure used, which is the highest published score for any method to date. Given the success of the method in CASP3, it is reasonable to be con®dent that the evaluation presented here gives a fair indication of the performance of the method in general.
A two-stage neural network has been used to predict protein secondary structure based on the posi... more A two-stage neural network has been used to predict protein secondary structure based on the position speci®c scoring matrices generated by PSI-BLAST. Despite the simplicity and convenience of the approach used, the results are found to be superior to those produced by other methods, including the popular PHD method according to our own benchmarking results and the results from the recent Critical Assessment of Techniques for Protein Structure Prediction experiment (CASP3), where the method was evaluated by stringent blind testing. Using a new testing set based on a set of 187 unique folds, and three-way cross-validation based on structural similarity criteria rather than sequence similarity criteria used previously (no similar folds were present in both the testing and training sets) the method presented here (PSIPRED) achieved an average Q 3 score of between 76.5 % to 78.3 % depending on the precise de®nition of observed secondary structure used, which is the highest published score for any method to date. Given the success of the method in CASP3, it is reasonable to be con®dent that the evaluation presented here gives a fair indication of the performance of the method in general.