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A Survey Road Map on Different Algorithms Proposed on Protein Structure Prediction

  • Kunal KabiEmail author
  • Bhabani Shankar Prasad Mishra
  • Satya Ranjan Dash
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 755)

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.

Keywords

Protein structure prediction Machine learning Artificial neural network Deep neural network 

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Further Reading

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    Tchoumatchenko, I., Vissotsky, F., Ganascia, J.-G.: How to make explicit a neural network trained to predict proteins secondary structure’. ACASA, LAFORIA-CNRS, Université Paris VI, 4 Place Jussieu, 75 252 Paris, CEDEX 05, France (1993)Google Scholar
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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Kunal Kabi
    • 1
    Email author
  • Bhabani Shankar Prasad Mishra
    • 1
  • Satya Ranjan Dash
    • 2
  1. 1.School of Computer EngineeringKIIT, Deemed to be UniversityBhubaneswarIndia
  2. 2.School of Computer ApplicationsKIIT, Deemed to be UniversityBhubaneswarIndia

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