PESPAD: a new tool for protein secondary structure prediction based on decision trees.
Main Article Content
Predicting the secondary structure of the protein is a central problem in bioinformatics. The problem is focused on try to predict the structure of each residue given the amino acid sequence. The most common secondary structures are helix and - sheets. Despite the progress made in making models for predicting the secondary structure, there is still a need to improve their predictive accuracy. This paper presents a new tool for predicting the secondary structure of the protein, called PESPAD, which significantly exceeds the accuracy of predictive methods available now. The tool is based on models constructed by using decision trees for the mixture of experts.
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