Protein structural class prediction via k-separated bigrams using position specific scoring matrix
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Protein structural class prediction (SCP) is as important task in identifying protein tertiary structure and protein functions. In this study, we propose a feature extraction technique to predict secondary structures. The technique utilizes bigram (of adjacent and k-separated amino acids) information derived from Position Specific Scoring Matrix (PSSM). The technique has shown promising results when evaluated on benchmarked Ding and Dubchak dataset.
Journal of Advanced Computational Intelligence and Intelligent Informatics
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Artificial Intelligence and Image Processing not elsewhere classified