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Solve DNA sequence assembly problem using hybrid crow search optimization and multi classification techniques

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Abstract

The reconstruction of a DNA chain from the randomly collected fragments set is known as the Deoxyribonucleic Acid Fragment Assembly Problem (DNA-FAP). In the genome project, this problem is usually considered an important step. Genome fragment assembly is the main objective in a much more important human genome sequence and helps to cure several genetic problems. Cost plays an important part in the process of genome fragment assembly. However, metaheuristics and machine learning model help to reduce the complexity level and error rates of genome assembly problem. The proposed work for hybrid Crow search optimization and multiple classifiers to calculate high similarity consensus sequence. The implementation result exhibits the proposed model produces better results and is compared with existing art techniques. This model performed types of benchmark datasets and provide different metric results in DNA sequence assembly.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India

    G. Raja

  2. Department of Computer Applications, National Institute of Technology, Trichy, India

    U. Srinivasulu Reddy

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  1. G. Raja
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  2. U. Srinivasulu Reddy
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Correspondence to G. Raja.

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Raja, G., Reddy, U.S. Solve DNA sequence assembly problem using hybrid crow search optimization and multi classification techniques. Int. j. inf. tecnol. 14, 2541–2547 (2022). https://doi.org/10.1007/s41870-022-00972-3

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  • DOI: https://doi.org/10.1007/s41870-022-00972-3

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