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Artigo de periodico
BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification (2024)
Santos, Anderson Paulo Avila ; Almeida, Breno Lívio Silva de ; Bonidia, Robson Parmezan ; Stadler, Peter F ; Štefanič, Polonca; Mandic-Mulec, Ines; Rocha, Ulisses Nunes da ; Sanches, Danilo Sipoli ; Carvalho, Andre Carlos Ponce de Leon Ferreira de
Source: RNA Biology. Unidades: ICMC, EESC E ICMC
Subjects: BIOINFORMÁTICA, APRENDIZAGEM PROFUNDA, REDES NEURAIS, RNA, REGULAÇÃO GÊNICA, GENÔMICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Anderson Paulo Avila et al. BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification. RNA Biology, v. 21, n. 1, p. 1-12, 2024Tradução . . Disponível em: https://doi.org/10.1080/15476286.2024.2329451. Acesso em: 31 out. 2024.
APA
Santos, A. P. A., Almeida, B. L. S. de, Bonidia, R. P., Stadler, P. F., Štefanič, P., Mandic-Mulec, I., et al. (2024). BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification. RNA Biology, 21( 1), 1-12. doi:10.1080/15476286.2024.2329451
NLM
Santos APA, Almeida BLS de, Bonidia RP, Stadler PF, Štefanič P, Mandic-Mulec I, Rocha UN da, Sanches DS, Carvalho ACP de LF de. BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification [Internet]. RNA Biology. 2024 ; 21( 1): 1-12.[citado 2024 out. 31 ] Available from: https://doi.org/10.1080/15476286.2024.2329451
Vancouver
Santos APA, Almeida BLS de, Bonidia RP, Stadler PF, Štefanič P, Mandic-Mulec I, Rocha UN da, Sanches DS, Carvalho ACP de LF de. BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification [Internet]. RNA Biology. 2024 ; 21( 1): 1-12.[citado 2024 out. 31 ] Available from: https://doi.org/10.1080/15476286.2024.2329451
Artigo de periodico
A novel decomposing model with evolutionary algorithms for feature selection in long non-coding RNAs (2020)
Bonidia, Robson Parmezan ; Machida, Jaqueline Sayuri; Negri, Tatianne Costa ; Alves, Wonder Alexandre Luz ; Kashiwabara, André Yoshiaki ; Domingues, Douglas S ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Paschoal, Alexandre Rossi ; Sanches, Danilo Sipoli
Source: IEEE Access. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, BIOINFORMÁTICA, HEURÍSTICA, ALGORITMOS GENÉTICOS, RNA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 31 out. 2024.
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 2024 out. 31 ] 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 2024 out. 31 ] Available from: https://doi.org/10.1109/ACCESS.2020.3028039
Trabalho de evento
Selecting the most relevant features for the identification of long non-coding RNAs in plants (2019)
Bonidia, Robson P ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Paschoal, Alexandre Rossi ; Sanches, Danilo Sipoli
Source: Proceedings. Conference titles: Brazilian Conference on Intelligent Systems - BRACIS. Unidade: ICMC
Subjects: BIOINFORMÁTICA, HEURÍSTICA, ALGORITMOS GENÉTICOS, APRENDIZADO COMPUTACIONAL, RNA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BONIDIA, Robson P et al. Selecting the most relevant features for the identification of long non-coding RNAs in plants. 2019, Anais.. Piscataway: IEEE, 2019. Disponível em: https://doi.org/10.1109/BRACIS.2019.00100. Acesso em: 31 out. 2024.
APA
Bonidia, R. P., Carvalho, A. C. P. de L. F. de, Paschoal, A. R., & Sanches, D. S. (2019). Selecting the most relevant features for the identification of long non-coding RNAs in plants. In Proceedings. Piscataway: IEEE. doi:10.1109/BRACIS.2019.00100
NLM
Bonidia RP, Carvalho ACP de LF de, Paschoal AR, Sanches DS. Selecting the most relevant features for the identification of long non-coding RNAs in plants [Internet]. Proceedings. 2019 ;[citado 2024 out. 31 ] Available from: https://doi.org/10.1109/BRACIS.2019.00100
Vancouver
Bonidia RP, Carvalho ACP de LF de, Paschoal AR, Sanches DS. Selecting the most relevant features for the identification of long non-coding RNAs in plants [Internet]. Proceedings. 2019 ;[citado 2024 out. 31 ] Available from: https://doi.org/10.1109/BRACIS.2019.00100

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