Predicting protein secondary structure by cascade-correlation neural networks.
basic_science · Level V
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Abstract
The back-propagation neural network algorithm is a commonly used method for predicting the secondary structure of proteins. Whilst popular, this method can be slow to learn and here we compare it with an alternative: the cascade-correlation architecture. Using a constructive algorithm, cascade-correlation achieves predictive accuracies comparable to those obtained by back-propagation, in shorter time.
Medical subject headings
- Algorithms
- Databases, Protein
- Models, Molecular
- Neural Networks, Computer
- Proteins
- Sequence Alignment
- Sequence Analysis, Protein