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Hybrid of PSO-GSA based Clustering Approach for Predicting Structural Class Prediction using Random Forest Method

    Authors

    • Sarneet Kaur 1
    • Ashok Sharma 2
    • Parveen Singh 3

    1 Computer Application, LPU University

    2 Computer Science, LPU University

    3 University of Jammu

,

Document Type : Research Article

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Abstract

Protein can be classified in different classes. A lot of research is being performed for analyzing the structure and classes of protein. There are many problems associated with protein structure. Some of them are folding problem and protein structure prediction (PSP) etc. PSP is the most considerable open problem in field of biology. In the present work different algorithms like particle swarm optimization (PSO), gravitational search algorithm (GSA) and K-Mean clustering algorithms are used to classify different structures of protein. A random forest (RF) classifier is proposed for analyzing and comparing different protein classes in terms of other conventionally available algorithms in terms of various performance parameters like accuracy, recall, precision and specificity. The proposed classifier proved better than other classifiers in terms of accuracy and can be helpful in predicting the protein structures. A hybrid PSO-GSA algorithm is also proposed which provided improved performance as compared to single algorithms and can be utilized for analysis of protein structure.

Keywords

  • Gravitational Search Algorithm
  • K-Mean Clustering Algorithm
  • Protein Structure Prediction
  • Particle swarm optimization
  • Random Forest Classifier
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European Journal of Molecular & Clinical Medicine
Volume 7, Issue 10
December 2020
Page 17-32
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  • Article View: 452
  • PDF Download: 504

APA

Kaur, S., Sharma, A., & Singh, P. (2020). Hybrid of PSO-GSA based Clustering Approach for Predicting Structural Class Prediction using Random Forest Method. European Journal of Molecular & Clinical Medicine, 7(10), 17-32.

MLA

Sarneet Kaur; Ashok Sharma; Parveen Singh. "Hybrid of PSO-GSA based Clustering Approach for Predicting Structural Class Prediction using Random Forest Method". European Journal of Molecular & Clinical Medicine, 7, 10, 2020, 17-32.

HARVARD

Kaur, S., Sharma, A., Singh, P. (2020). 'Hybrid of PSO-GSA based Clustering Approach for Predicting Structural Class Prediction using Random Forest Method', European Journal of Molecular & Clinical Medicine, 7(10), pp. 17-32.

VANCOUVER

Kaur, S., Sharma, A., Singh, P. Hybrid of PSO-GSA based Clustering Approach for Predicting Structural Class Prediction using Random Forest Method. European Journal of Molecular & Clinical Medicine, 2020; 7(10): 17-32.

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