Abstract
As a result of the increasing interest on genomic signal processing, there is the necessity of develop computational software that combines different tools for signal processing and automatic analysis. This paper presents a computational tool for mapping and clustering DNA sequences. Several DNA numerical representations, a feature extraction method, the K-means algorithm and different clustering evaluation metrics were implemented. This software allows to researchers to perform genomic signal analysis through a graphical user interface, without need programming skills. The tool is prepared to increase their capabilities by implementing different algorithms or modules. Also, a comparative analysis of eleven DNA numerical representation is presented. The results show that Electron-ion and Voss present the best performances when clustering genomic signals using K-means. The clusters quality was measure using the ARI metric.
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Ramírez, V., Román-Godínez, I., Torres-Ramos, S. (2020). DNA-MC: Tool for Mapping and Clustering DNA Sequences. In: González Díaz, C., et al. VIII Latin American Conference on Biomedical Engineering and XLII National Conference on Biomedical Engineering. CLAIB 2019. IFMBE Proceedings, vol 75. Springer, Cham. https://doi.org/10.1007/978-3-030-30648-9_98
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DOI: https://doi.org/10.1007/978-3-030-30648-9_98
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