Protein Structure Classification Based on Distance Feature

Authors

  • Dr. Sheshang Degadwala  Associate Professor, Computer Engineering, Sigma Institute of Engineering, Vadodara, Gujarat, India
  • Dhairya Vyas  Managing Director, Shree Drashti Infotech LLP, Vadodara, Gujarat, India
  • Harsh S Dave   Intern MBBS, Smt.B.K.Shah Medical Institute &Research Centre, Vadodara, Gujarat, India

DOI:

https://doi.org/10.32628/CSEIT206464

Keywords:

Protein, Structure, Distance, Amino Acid, Sequence, SVM (Support Vector Machine), DT (Decision Tree), ANN (Artificial Neural Network), NB (Naive Bayer).

Abstract

In Bioinformatics field Protein Structure Classification is the hugest undertaking. The realized proteins have been requested subject to their level, feature, work, amino destructive and family and superfamily. Protein structure segregated into four sorts: all ? protein structure, all ? protein structure, ?+? protein structure, and ?/? protein structure. The use of a standard way to deal with perform plan is a very inconvenient and dreary task. The quantity of cutting edge Machine Intelligence enrolling strategies such Support Vector Machine, Random Forest, Artificial Neural Network, Decision Tree and Naïve Bayes Classifier had been proposed in the composition. Our objective right currently is to develop a system that performs better than anything past markers for protein structure gathering by thinking about the separation among the distinctive Amino Acid buildups. To take a gander at the display of proposed work particular datasets are used.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2020-07-30

Issue

Volume 6, Issue 4, July-August-2020

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. Sheshang Degadwala, Dhairya Vyas, Harsh S Dave , " Protein Structure Classification Based on Distance Feature" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 4, pp.263-269, July-August-2020. Available at doi : https://doi.org/10.32628/CSEIT206464