Analysis of Protein Structure for Drug Repurposing Using Computational Intelligence and ML Algorithm
| Autor: | Deepak Srivastava, Kwok Tai Chui, Varsha Arya, Francisco José García Peñalvo, Pramod Kumar, Anuj Kumar Singh |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | International Journal of Software Science and Computational Intelligence. 14:1-11 |
| ISSN: | 1942-9037 1942-9045 |
| DOI: | 10.4018/ijssci.312562 |
| Popis: | Proteins are fundamental compounds in biological processes during the analysis of drug target indication for drug repurposing. The identification of relevant features is a necessary step in determining protein structure. A classification technique is used to identify the most important features in a dataset, which is why feature selection is so important. For protein structure prediction, recent research has developed a wide range of new methods to improve accuracy. The authors use principal component analysis (PCA) with correlation-matrix-based feature selection to analyse breast cancer data. In this paper, they discussed a therapeutic agent that is used to reduce the dataset by reduction-based algorithm and after that applied reduced dataset labelled as Standard Gold Dataset on machine learning model to analyze drug target indication. They get the higher accuracy of 92.8%, 93.9%, and 95.3%, each of the three datasets with 200, 500, and 1000 features with SVM with RBF kernel function. Also they found the best result, 97.8%, with the same classifier. |
| Databáze: | OpenAIRE |
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