A novel decomposing model with evolutionary algorithms for feature selection in long non-coding RNAs (2020)
- Authors:
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; BONIDIA, ROBSON PARMEZAN - ICMC
- Unidade: ICMC
- DOI: 10.1109/ACCESS.2020.3028039
- Subjects: APRENDIZADO COMPUTACIONAL; BIOINFORMÁTICA; HEURÍSTICA; ALGORITMOS GENÉTICOS; RNA
- Keywords: Feature selection; Metaheuristic
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Piscataway
- Date published: 2020
- Source:
- Título: IEEE Access
- ISSN: 2169-3536
- Volume/Número/Paginação/Ano: v. 8, p. 181683-181697, 2020
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
BONIDIA, Robson Parmezan et al. A novel decomposing model with evolutionary algorithms for feature selection in long non-coding RNAs. IEEE Access, v. 8, p. 181683-181697, 2020Tradução . . Disponível em: https://doi.org/10.1109/ACCESS.2020.3028039. Acesso em: 10 fev. 2026. -
APA
Bonidia, R. P., Machida, J. S., Negri, T. C., Alves, W. A. L., Kashiwabara, A. Y., Domingues, D. S., et al. (2020). A novel decomposing model with evolutionary algorithms for feature selection in long non-coding RNAs. IEEE Access, 8, 181683-181697. doi:10.1109/ACCESS.2020.3028039 -
NLM
Bonidia RP, Machida JS, Negri TC, Alves WAL, Kashiwabara AY, Domingues DS, Carvalho ACP de LF de, Paschoal AR, Sanches DS. A novel decomposing model with evolutionary algorithms for feature selection in long non-coding RNAs [Internet]. IEEE Access. 2020 ; 8 181683-181697.[citado 2026 fev. 10 ] Available from: https://doi.org/10.1109/ACCESS.2020.3028039 -
Vancouver
Bonidia RP, Machida JS, Negri TC, Alves WAL, Kashiwabara AY, Domingues DS, Carvalho ACP de LF de, Paschoal AR, Sanches DS. A novel decomposing model with evolutionary algorithms for feature selection in long non-coding RNAs [Internet]. IEEE Access. 2020 ; 8 181683-181697.[citado 2026 fev. 10 ] Available from: https://doi.org/10.1109/ACCESS.2020.3028039 - BioAutoML: democratizing machine learning in life sciences
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Informações sobre o DOI: 10.1109/ACCESS.2020.3028039 (Fonte: oaDOI API)
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