Evento

A Memetic Cellular Genetic Algorithm for Multiple Sequence Alignment

Rojas, Matias Gabriel Icon; Carballido, Jessica Andrea Icon; Olivera, Ana Carolina Icon; Vidal, Pablo Javier Icon

Otros responsables

Fecha

2020

Editorial

Institute of Electrical and Electronics Engineers

Revista

Título del libro

Nombre del evento

V IEEE Congreso Bienal de Argentina

Fecha del evento

2020-12-01

Institución organizadora

Institute of Electrical and Electronics Engineers
Universidad Tecnológica Nacional. Facultad Regional Resistencia

ISSN

eISSN

ISBN

978-1-7281-5957-7

Idioma

Español

Tipo del evento

Congreso

Resumen

Multiple sequence alignment consists in the match of three or more sequences at the aim to discover both their shared and unshared areas. Multiple sequence alignment is frequently used for several activities of the biological sciences such as drugs finding, cancer study, and epidemiologic analysis. Thus it results fundamental. Nevertheless, the more sequences it has to align the more computational complexity it represents, so it is crucial to identify techniques that get good results at the same time they do good use of the resources. In this work, a memetic cellular genetic algorithm is presented to solve the multiple sequence alignment problem. The results have shown that our proposal can obtain good results keeping good performance in resources use.

Aprobación

Revisión

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Licencia Creative Commons

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