loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Geraldo Francisco Donegá Zafalon 1 ; 2 ; Vitoria Zanon Gomes 2 ; Anderson Rici Amorim 3 ; 2 and Carlos Roberto Valêncio 2

Affiliations: 1 Department ICET, Universidade Paulista, Avenida Presidente Juscelino Kubitschek de Oliveira, s/n, Jardim Tarraf II, São José do Rio Preto, SP, 15091-450, Brazil ; 2 Department of Computer Science and Statistics, Universidade Estadual Paulista (UNESP), Rua Cristóvão Colombo, 2265, Jardim Nazareth, São José do Rio Preto, SP, 15054-000, Brazil ; 3 Department of Computer and Digital Systems Engineering, Universidade de São Paulo (USP), Escola Politécnica, Av. Prof. Luciano Gualberto, Travessa 3, 158, Butantã, São Paulo, SP, 05508-010, Brazil

Keyword(s): Genetic Algorithm, Multiple Sequence Alignment, Hybrid Multiple Sequence Alignment, Bioinformatics.

Abstract: The multiple sequence alignment is one of the main tasks in bioinformatics. It is used in different important biological analysis, such as function and structure prediction of unknown proteins. There are several approaches to perform multiple sequence alignment and the use of heuristics and meta-heuristics stands out because of the search ability of these methods, which generally leads to good results in a reasonable amount of time. The progressive alignment and genetic algorithm are among the most used heuristics and meta-heuristics to perform multiple sequence alignment. However, both methods have disadvantages, such as error propagation in the case of progressive alignment and local optima results in the case of genetics algorithm. Thus, this work proposes a new hybrid refinement phase using a progressive approach to locally realign the multiple sequence alignment produced by genetic algorithm based tools. Our results show that our method is able to improve the quality of the alig nments of all families from BAliBase. Considering Q and TC quality measures from BaliBase, we have obtained the improvements of 55% for Q and 167% for TC. Then, with these results we can provide more biologically significant results. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.145.112.217

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Zafalon, G.; Gomes, V.; Amorim, A. and Valêncio, C. (2021). A Hybrid Approach using Progressive and Genetic Algorithms for Improvements in Multiple Sequence Alignments. In Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-509-8; ISSN 2184-4992, SciTePress, pages 384-391. DOI: 10.5220/0010495303840391

@conference{iceis21,
author={Geraldo Francisco Donegá Zafalon. and Vitoria Zanon Gomes. and Anderson Rici Amorim. and Carlos Roberto Valêncio.},
title={A Hybrid Approach using Progressive and Genetic Algorithms for Improvements in Multiple Sequence Alignments},
booktitle={Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2021},
pages={384-391},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010495303840391},
isbn={978-989-758-509-8},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - A Hybrid Approach using Progressive and Genetic Algorithms for Improvements in Multiple Sequence Alignments
SN - 978-989-758-509-8
IS - 2184-4992
AU - Zafalon, G.
AU - Gomes, V.
AU - Amorim, A.
AU - Valêncio, C.
PY - 2021
SP - 384
EP - 391
DO - 10.5220/0010495303840391
PB - SciTePress