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Dynamic scaling factor based differential evolution with multi-layer perceptron for gene selection from pathway information of microarray data

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Abstract

The microarray data contains the high volume of genes having multiple values of expressions and small number of samples. Therefore, the selection of gene from microarray data is an extremely challenging and important issue to analyze the biological behavior of features. In this context, dynamic scaling factor based differential evolution (DE) with multi-layer perceptron (MLP) is designed for selection of genes from pathway information of microarray data. At first DE is employed to select the relevant and lesser number of genes. Then MLP is used to build a classifier model over the selected genes. A suitable and efficient representation of vector is designed for DE. The fitness function is derived separately as T-score, classification accuracy and weight sum approach of both. Simulation and further analysis is performed in terms of sensitivity, specificity, accuracy and F-score. Moreover, statistical and biological analysis are also conducted.

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  1. Department of Computer Science & Engineering, National Institute of Technology Sikkim, Ravangla, 737139, Sikkim, India

    Pintu Kumar Ram & Pratyay Kuila

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  1. Pintu Kumar Ram
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  2. Pratyay Kuila
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Correspondence to Pintu Kumar Ram.

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Ram, P.K., Kuila, P. Dynamic scaling factor based differential evolution with multi-layer perceptron for gene selection from pathway information of microarray data. Multimed Tools Appl 82, 13453–13478 (2023). https://doi.org/10.1007/s11042-022-13964-z

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  • DOI: https://doi.org/10.1007/s11042-022-13964-z

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