A Memetic Cellular Genetic Algorithm for Multiple Sequence Alignment
; Carballido, Jessica Andrea
; Olivera, Ana Carolina
; Vidal, Pablo Javier 
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
Universidad Tecnológica Nacional. Facultad Regional Resistencia
ISSN
eISSN
ISBN
978-1-7281-5957-7
Idioma
Español
Tipo del evento
Congreso
Clasificación temática
Palabras clave
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.
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