Abstract
The protein is not just a simple word. It is a backbone of every living organism from small to big. Protein monomer units consist of structures which are constructed by some definite process which is called protein folding. Protein folding process gives brief idea about the sequence’s structural occurrence from primary to quaternary state. In this process one important aspect is protein structure prediction which helps predicting the structural formation from a previous structural state. In bioinformatics field most researchers concentrate on protein structure prediction for better drug discovery. In this paper, we studied the protein secondary structure prediction using different algorithms like simple Artificial Neural Network (ANN), Machine Learning (ML) with multiple ANN (ML-ANN), and Deep Neural Network (DNN) in Restricted Boltzman Machine(RBM) on one dataset called Protein Data Bank (PDB). We compare the accuracy result of these three techniques with the same dataset.
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Further Reading
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Kabi, K., Mishra, B.S.P., Dash, S.R. (2019). A Survey Road Map on Different Algorithms Proposed on Protein Structure Prediction. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-13-1951-8_35
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DOI: https://doi.org/10.1007/978-981-13-1951-8_35
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