A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CHIARI, Laise Pellegrini Alencar et al. A PLS study on the psychotropic activity for a series of cannabinoid compounds. Journal of Molecular Modeling, v. 29, 2023Tradução . . Disponível em: https://doi.org/10.1007/s00894-023-05443-5. Acesso em: 04 ago. 2024.
APA
Chiari, L. P. A., Silva, A. P. da, Honorio, K. M., & Silva, A. B. F. da. (2023). A PLS study on the psychotropic activity for a series of cannabinoid compounds. Journal of Molecular Modeling, 29. doi:10.1007/s00894-023-05443-5
NLM
Chiari LPA, Silva AP da, Honorio KM, Silva ABF da. A PLS study on the psychotropic activity for a series of cannabinoid compounds [Internet]. Journal of Molecular Modeling. 2023 ; 29[citado 2024 ago. 04 ] Available from: https://doi.org/10.1007/s00894-023-05443-5
Vancouver
Chiari LPA, Silva AP da, Honorio KM, Silva ABF da. A PLS study on the psychotropic activity for a series of cannabinoid compounds [Internet]. Journal of Molecular Modeling. 2023 ; 29[citado 2024 ago. 04 ] Available from: https://doi.org/10.1007/s00894-023-05443-5
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SANTOS, Genisson R. et al. A partial least squares and artifcial neural network study for a series of arylpiperazines as antidepressant agents. Journal of Molecular Modeling: computational chemistry - life science - advanced materials - new methods, p. 297, 2021Tradução . . Disponível em: https://doi.org/10.1007/s00894-021-04906-x. Acesso em: 04 ago. 2024.
APA
Santos, G. R., Chiari, L. P. A., Silva, A. P. da, Lipinski, C. F., Oliveira, A. A., Honório, K. M., et al. (2021). A partial least squares and artifcial neural network study for a series of arylpiperazines as antidepressant agents. Journal of Molecular Modeling: computational chemistry - life science - advanced materials - new methods, 297. doi:10.1007/s00894-021-04906-x
NLM
Santos GR, Chiari LPA, Silva AP da, Lipinski CF, Oliveira AA, Honório KM, Sousa AG de, Silva ABF da. A partial least squares and artifcial neural network study for a series of arylpiperazines as antidepressant agents [Internet]. Journal of Molecular Modeling: computational chemistry - life science - advanced materials - new methods. 2021 ;297.[citado 2024 ago. 04 ] Available from: https://doi.org/10.1007/s00894-021-04906-x
Vancouver
Santos GR, Chiari LPA, Silva AP da, Lipinski CF, Oliveira AA, Honório KM, Sousa AG de, Silva ABF da. A partial least squares and artifcial neural network study for a series of arylpiperazines as antidepressant agents [Internet]. Journal of Molecular Modeling: computational chemistry - life science - advanced materials - new methods. 2021 ;297.[citado 2024 ago. 04 ] Available from: https://doi.org/10.1007/s00894-021-04906-x
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
ALMEIDA, Michell de Oliveira e FARIA, Sérgio H. D. M e HONÓRIO, Káthia Maria. An electronic point of view on the inhibition of ALK‑5 by bioactive candidates related to cancer. Theoretical Chemistry Accounts, v. 139, n. 91, p. 1-16 on line 06 May 2020, 2020Tradução . . Disponível em: https://doi.org/10.1007/s00214-020-02602-2. Acesso em: 04 ago. 2024.
APA
Almeida, M. de O., Faria, S. H. D. M., & Honório, K. M. (2020). An electronic point of view on the inhibition of ALK‑5 by bioactive candidates related to cancer. Theoretical Chemistry Accounts, 139( 91), 1-16 on line 06 May 2020. doi:10.1007/s00214-020-02602-2
NLM
Almeida M de O, Faria SHDM, Honório KM. An electronic point of view on the inhibition of ALK‑5 by bioactive candidates related to cancer [Internet]. Theoretical Chemistry Accounts. 2020 ; 139( 91): 1-16 on line 06 May 2020.[citado 2024 ago. 04 ] Available from: https://doi.org/10.1007/s00214-020-02602-2
Vancouver
Almeida M de O, Faria SHDM, Honório KM. An electronic point of view on the inhibition of ALK‑5 by bioactive candidates related to cancer [Internet]. Theoretical Chemistry Accounts. 2020 ; 139( 91): 1-16 on line 06 May 2020.[citado 2024 ago. 04 ] Available from: https://doi.org/10.1007/s00214-020-02602-2