A Memetic Cellular Genetic Algorithm for Multiple Sequence Alignment

ROJAS MATÍAS GABRIEL; JESSICA ANDREA CARBALLIDO; ANA CAROLINA OLIVERA; PABLO JAVIER VIDAL

Resistencia, Chaco

Congreso; V Congreso Bienal de la Sección Argentina del IEEE; 2020

Facultad Regional Resistencia, Universidad Tecnológica Nacional.

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.