A Hybrid Genetic Algorithm using Progressive Alignment and Consistency based Approach for Multiple Sequence Alignments

Vitoria Gomes, Matheus Andrade, Anderson Amorim, Anderson Amorim, Geraldo Zafalon, Geraldo Zafalon

2022

Abstract

The multiple sequence alignment is one of the most important tasks in bioinformatics, since it allows to analyze multiple sequences at the same time. There are many approaches for this problem such as heuristics and metaheuristics, that generally lead to great results in a plausible time, being among the most used approaches. The genetic algorithm is one of the most used methods because of its results quality, but it had a problematic disadvantage: it can be easily trapped in a local optima result, not being able to reach better alignments. In this work we propose a hybrid genetic algorithm with progressive and consistency-based methods as a way to smooth the local optima problem and improve the quality of the alignments. The obtained results show that our method was able to improve the quality of AG results 2 a 27 times, smoothing the local maximum problem and providing results with more biological significance.

Paper Citation

in Harvard Style

Gomes V., Andrade M., Amorim A. and Zafalon G. (2022). A Hybrid Genetic Algorithm using Progressive Alignment and Consistency based Approach for Multiple Sequence Alignments. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-569-2, pages 167-174. DOI: 10.5220/0011082900003179

in Bibtex Style

@conference{iceis22,
author={Vitoria Gomes and Matheus Andrade and Anderson Amorim and Geraldo Zafalon},
title={A Hybrid Genetic Algorithm using Progressive Alignment and Consistency based Approach for Multiple Sequence Alignments},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2022},
pages={167-174},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011082900003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Hybrid Genetic Algorithm using Progressive Alignment and Consistency based Approach for Multiple Sequence Alignments
SN - 978-989-758-569-2
AU - Gomes V.
AU - Andrade M.
AU - Amorim A.
AU - Zafalon G.
PY - 2022
SP - 167
EP - 174
DO - 10.5220/0011082900003179