Pattern Recognition in Biosequences Using Artificial Immune System

Luiz Paulo Liberato, Álvaro Nogueira da Cruz, Anderson Amorim, Vitoria Gomes, Bruno Rodrigues da Silveira, Gabriel Augusto Prevato, Luiza Guimarães Cavarçan, Carlos Valêncio, Geraldo Zafalon

2025

Abstract

With the advance on genomic studies was possible to know better the genetic inheritance, protein synthesis and mutations that occurs in living beings. With the increase in the DNA sequencing capacity, and its storage, advanced biological studies are possible. To ensure timely and greater precision in the pattern recognition process, heuristic methods are used, since deterministic methods make it impossible to execute large volumes of data. Heuristic methods have the characteristic of seeking the best possible solution within the search space that is explored. Among the known heuristics is the Artificial Immune System (AIS), which falls under the category of bioinspired methods that simulate biological behavior. In this work, the CLONALG (Clonal Selection Algorithm) of the AIS approach was implemented with HMM (Hidden Markov Model) as an affinity function, in order to obtain stochastic patterns with biological relevance and an acceptable computational time. As a result, a 50% more relevant value was obtained in terms of execution time, when compared to CLONALG with the Hamming affinity function. Finally, it was also validated that CLONALG with the HMM implementation was able to recognize the same patterns when compared to similar tools.

Paper Citation

in Harvard Style

Liberato L., Nogueira da Cruz Á., Amorim A., Gomes V., Rodrigues da Silveira B., Prevato G., Cavarçan L., Valêncio C. and Zafalon G. (2025). Pattern Recognition in Biosequences Using Artificial Immune System. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 797-804. DOI: 10.5220/0013293500003929

in Bibtex Style

@conference{iceis25,
author={Luiz Liberato and Álvaro Nogueira da Cruz and Anderson Amorim and Vitoria Gomes and Bruno Rodrigues da Silveira and Gabriel Prevato and Luiza Cavarçan and Carlos Valêncio and Geraldo Zafalon},
title={Pattern Recognition in Biosequences Using Artificial Immune System},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2025},
pages={797-804},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013293500003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Pattern Recognition in Biosequences Using Artificial Immune System
SN - 978-989-758-749-8
AU - Liberato L.
AU - Nogueira da Cruz Á.
AU - Amorim A.
AU - Gomes V.
AU - Rodrigues da Silveira B.
AU - Prevato G.
AU - Cavarçan L.
AU - Valêncio C.
AU - Zafalon G.
PY - 2025
SP - 797
EP - 804
DO - 10.5220/0013293500003929
PB - SciTePress