Jaehee Hong
ABSTRACT
In this research, the learning based solely on amino acid sequences were conducted using ANN. By considering various conditions such as window size, dropout, optimizer, etc., it was shown that the highest accuracy of predicting whether the amino acid is part of α-helix or not was about 74%, and whether the amino acid is part of α-helix, β-sheet or the other structures was about 50%. Our model has a limitation that highest accuracy is bound to a certain value. However, it has a significance of embodying the protein secondary structure prediction model that learns only from amino acid sequences; it is simpler than multiple sequence alignment, the widely used method in protein secondary structure prediction.
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Index Terms
- Protein Secondary Structure Prediction from Amino Acid Sequence Using Artificial Neural Network
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