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Artigo de periodico
MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical (2022)
Bonidia, Robson Parmezan ; Domingues, Douglas S ; Sanches, Danilo Sipoli ; Carvalho, André Carlos Ponce de Leon Ferreira de
Source: Briefings in Bioinformatics. Unidade: ICMC
Subjects: BIOINFORMÁTICA, APRENDIZADO COMPUTACIONAL, PYTHON
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BONIDIA, Robson Parmezan et al. MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical. Briefings in Bioinformatics, v. 23, n. 1, p. 1-10, 2022Tradução . . Disponível em: https://doi.org/10.1093/bib/bbab434. Acesso em: 14 maio 2024.
APA
Bonidia, R. P., Domingues, D. S., Sanches, D. S., & Carvalho, A. C. P. de L. F. de. (2022). MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical. Briefings in Bioinformatics, 23( 1), 1-10. doi:10.1093/bib/bbab434
NLM
Bonidia RP, Domingues DS, Sanches DS, Carvalho ACP de LF de. MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical [Internet]. Briefings in Bioinformatics. 2022 ; 23( 1): 1-10.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbab434
Vancouver
Bonidia RP, Domingues DS, Sanches DS, Carvalho ACP de LF de. MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical [Internet]. Briefings in Bioinformatics. 2022 ; 23( 1): 1-10.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbab434
Artigo de periodico
CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts (2021)
Nachtigall, Pedro Gabriel ; Kashiwabara, André Yoshiaki ; Durham, Alan Mitchell
Source: Briefings in Bioinformatics. Unidade: IME
Subjects: BIOINFORMÁTICA, SEQUENCIAMENTO GENÉTICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NACHTIGALL, Pedro Gabriel e KASHIWABARA, André Yoshiaki e DURHAM, Alan Mitchell. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, v. 22, n. 3, p. 1-11, 2021Tradução . . Disponível em: https://doi.org/10.1093/bib/bbaa045. Acesso em: 14 maio 2024.
APA
Nachtigall, P. G., Kashiwabara, A. Y., & Durham, A. M. (2021). CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts. Briefings in Bioinformatics, 22( 3), 1-11. doi:10.1093/bib/bbaa045
NLM
Nachtigall PG, Kashiwabara AY, Durham AM. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts [Internet]. Briefings in Bioinformatics. 2021 ; 22( 3): 1-11.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbaa045
Vancouver
Nachtigall PG, Kashiwabara AY, Durham AM. CodAn: predictive models for precise identification of coding regions in eukaryotic transcripts [Internet]. Briefings in Bioinformatics. 2021 ; 22( 3): 1-11.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbaa045
Artigo de periodico
Feature extraction approaches for biological sequences: a comparative study of mathematical features (2021)
Bonidia, Robson Parmezan ; Sampaio, Lucas Dias Hiera ; Domingues, Douglas S ; Paschoal, Alexandre Rossi ; Lopes, Fabrício Martins ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Sanches, Danilo Sipoli
Source: Briefings in Bioinformatics. Unidade: ICMC
Subjects: BIOINFORMÁTICA, GENÔMICA, REDES COMPLEXAS, ENTROPIA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BONIDIA, Robson Parmezan et al. Feature extraction approaches for biological sequences: a comparative study of mathematical features. Briefings in Bioinformatics, v. 22, n. 5, p. Se 2021, 2021Tradução . . Disponível em: https://doi.org/10.1093/bib/bbab011. Acesso em: 14 maio 2024.
APA
Bonidia, R. P., Sampaio, L. D. H., Domingues, D. S., Paschoal, A. R., Lopes, F. M., Carvalho, A. C. P. de L. F. de, & Sanches, D. S. (2021). Feature extraction approaches for biological sequences: a comparative study of mathematical features. Briefings in Bioinformatics, 22( 5), Se 2021. doi:10.1093/bib/bbab011
NLM
Bonidia RP, Sampaio LDH, Domingues DS, Paschoal AR, Lopes FM, Carvalho ACP de LF de, Sanches DS. Feature extraction approaches for biological sequences: a comparative study of mathematical features [Internet]. Briefings in Bioinformatics. 2021 ; 22( 5): Se 2021.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbab011
Vancouver
Bonidia RP, Sampaio LDH, Domingues DS, Paschoal AR, Lopes FM, Carvalho ACP de LF de, Sanches DS. Feature extraction approaches for biological sequences: a comparative study of mathematical features [Internet]. Briefings in Bioinformatics. 2021 ; 22( 5): Se 2021.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbab011
Artigo de periodico
TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes (2021)
Oliveira, Mauro de Medeiros ; Bonadio, Ígor ; Melo, Alícia Lie de ; Souza, Gláucia Mendes ; Durham, Alan Mitchell
Source: Briefings in Bioinformatics. Unidades: IQ, IME, BIOINFORMÁTICA
Subjects: TRANSCRIÇÃO GÊNICA, BIOINFORMÁTICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Mauro de Medeiros et al. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes. Briefings in Bioinformatics, v. 22, n. 6, p. 1-12, 2021Tradução . . Disponível em: https://doi.org/10.1093/bib/bbab198. Acesso em: 14 maio 2024.
APA
Oliveira, M. de M., Bonadio, Í., Melo, A. L. de, Souza, G. M., & Durham, A. M. (2021). TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes. Briefings in Bioinformatics, 22( 6), 1-12. doi:10.1093/bib/bbab198
NLM
Oliveira M de M, Bonadio Í, Melo AL de, Souza GM, Durham AM. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes [Internet]. Briefings in Bioinformatics. 2021 ; 22( 6): 1-12.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbab198
Vancouver
Oliveira M de M, Bonadio Í, Melo AL de, Souza GM, Durham AM. TSSFinder—fast and accurate ab initio prediction of the core promoter in eukaryotic genomes [Internet]. Briefings in Bioinformatics. 2021 ; 22( 6): 1-12.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbab198
Artigo de periodico
Machine learning meets genome assembly (2019)
Souza, Kleber Padovani de; Setubal, Joao Carlos ; Carvalho, André Carlos Ponce de Leon Ferreira de ; Oliveira, Guilherme; Chateau, Annie; Alves, Ronnie
Source: Briefings in Bioinformatics. Unidades: IQ, ICMC
Subjects: APRENDIZADO COMPUTACIONAL, SEQUENCIAMENTO GENÉTICO
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUZA, Kleber Padovani de et al. Machine learning meets genome assembly. Briefings in Bioinformatics, v. No 2019, n. 6, p. 2116-2129, 2019Tradução . . Disponível em: https://doi.org/10.1093/bib/bby072. Acesso em: 14 maio 2024.
APA
Souza, K. P. de, Setubal, J. C., Carvalho, A. C. P. de L. F. de, Oliveira, G., Chateau, A., & Alves, R. (2019). Machine learning meets genome assembly. Briefings in Bioinformatics, No 2019( 6), 2116-2129. doi:10.1093/bib/bby072
NLM
Souza KP de, Setubal JC, Carvalho ACP de LF de, Oliveira G, Chateau A, Alves R. Machine learning meets genome assembly [Internet]. Briefings in Bioinformatics. 2019 ; No 2019( 6): 2116-2129.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bby072
Vancouver
Souza KP de, Setubal JC, Carvalho ACP de LF de, Oliveira G, Chateau A, Alves R. Machine learning meets genome assembly [Internet]. Briefings in Bioinformatics. 2019 ; No 2019( 6): 2116-2129.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bby072
Artigo de periodico
A comparative study of statistical methods used to identify dependencies between gene expression signals (2014)
Santos, Suzana de Siqueira ; Takahashi, Daniel Yasumasa ; Nakata, Asuka; Fujita, André
Source: Briefings in Bioinformatics. Unidade: IME
Subjects: BIOINFORMÁTICA, ESTATÍSTICA COMPUTACIONAL, CORRELAÇÃO GENÉTICA E AMBIENTAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Suzana de Siqueira et al. A comparative study of statistical methods used to identify dependencies between gene expression signals. Briefings in Bioinformatics, v. 15, n. 6, p. 906-918, 2014Tradução . . Disponível em: https://doi.org/10.1093/bib/bbt051. Acesso em: 14 maio 2024.
APA
Santos, S. de S., Takahashi, D. Y., Nakata, A., & Fujita, A. (2014). A comparative study of statistical methods used to identify dependencies between gene expression signals. Briefings in Bioinformatics, 15( 6), 906-918. doi:10.1093/bib/bbt051
NLM
Santos S de S, Takahashi DY, Nakata A, Fujita A. A comparative study of statistical methods used to identify dependencies between gene expression signals [Internet]. Briefings in Bioinformatics. 2014 ; 15( 6): 906-918.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbt051
Vancouver
Santos S de S, Takahashi DY, Nakata A, Fujita A. A comparative study of statistical methods used to identify dependencies between gene expression signals [Internet]. Briefings in Bioinformatics. 2014 ; 15( 6): 906-918.[citado 2024 maio 14 ] Available from: https://doi.org/10.1093/bib/bbt051

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