ReP USP - Resultado da busca

Artigo de periodico
Quantum machine learning algorithms for drug discovery applications (2021)
Batra, Kushal; Zorn, Kimberley M.; Foil, Daniel H.; Minerali, Eni; Gawriljuk, Victor Oliveira; Lane, Thomas R.; Ekins, Sean
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: PLANEJAMENTO DE FÁRMACOS, COMPUTAÇÃO APLICADA, INTELIGÊNCIA ARTIFICIAL
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BATRA, Kushal et al. Quantum machine learning algorithms for drug discovery applications. Journal of Chemical Information and Modeling, v. 61, n. 6, p. 2641-2647, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00166. Acesso em: 08 out. 2025.
APA
Batra, K., Zorn, K. M., Foil, D. H., Minerali, E., Gawriljuk, V. O., Lane, T. R., & Ekins, S. (2021). Quantum machine learning algorithms for drug discovery applications. Journal of Chemical Information and Modeling, 61( 6), 2641-2647. doi:10.1021/acs.jcim.1c00166
NLM
Batra K, Zorn KM, Foil DH, Minerali E, Gawriljuk VO, Lane TR, Ekins S. Quantum machine learning algorithms for drug discovery applications [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 6): 2641-2647.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00166
Vancouver
Batra K, Zorn KM, Foil DH, Minerali E, Gawriljuk VO, Lane TR, Ekins S. Quantum machine learning algorithms for drug discovery applications [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 6): 2641-2647.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00166
Artigo de periodico
Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus (2021)
Oliveira, Victor Gawriljuk Ferraro; Foil, Daniel H.; Puhl, Ana C. ; Zorn, Kimberley M.; Lane, Thomas R.; Riabova, Olga; Makarov, Vadim; Godoy, Andre Schutzer de ; Oliva, Glaucius ; Ekins, Sean
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: FEBRE AMARELA, APRENDIZADO COMPUTACIONAL, PLANEJAMENTO DE FÁRMACOS, ANTIVIRAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Victor Gawriljuk Ferraro et al. Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus. Journal of Chemical Information and Modeling, v. 61, n. 8, p. 3804-3813, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00460. Acesso em: 08 out. 2025.
APA
Oliveira, V. G. F., Foil, D. H., Puhl, A. C., Zorn, K. M., Lane, T. R., Riabova, O., et al. (2021). Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus. Journal of Chemical Information and Modeling, 61( 8), 3804-3813. doi:10.1021/acs.jcim.1c00460
NLM
Oliveira VGF, Foil DH, Puhl AC, Zorn KM, Lane TR, Riabova O, Makarov V, Godoy AS de, Oliva G, Ekins S. Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 8): 3804-3813.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00460
Vancouver
Oliveira VGF, Foil DH, Puhl AC, Zorn KM, Lane TR, Riabova O, Makarov V, Godoy AS de, Oliva G, Ekins S. Development of machine learning models and the discovery of a new antiviral compound against yellow fever virus [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 8): 3804-3813.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00460
Artigo de periodico
Machine learning models identify inhibitors of SARS-CoV2 (2021)
Oliveira, Victor Gawriljuk Ferraro; Zin, Phyo Phyo Kyaw; Puhl, Ana C. ; Zorn, Kimberley M.; Foil, Daniel H.; Lane, Thomas R.; Hurst, Brett; Tavella, Tatyana Almeida; Costa, Fabio Trindade Maranhão; Lakshmanane, Premkumar; Bernatchez, Jean; Godoy, Andre Schutzer de ; Oliva, Glaucius ; Siqueira-Neto, Jair L.; Madrid, Peter B.; Ekins, Sean
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: CORONAVIRUS, COVID-19, APRENDIZADO COMPUTACIONAL, PLANEJAMENTO DE FÁRMACOS, ANTIVIRAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
OLIVEIRA, Victor Gawriljuk Ferraro et al. Machine learning models identify inhibitors of SARS-CoV2. Journal of Chemical Information and Modeling, v. 61, n. 9, p. 4224-4235, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c00683. Acesso em: 08 out. 2025.
APA
Oliveira, V. G. F., Zin, P. P. K., Puhl, A. C., Zorn, K. M., Foil, D. H., Lane, T. R., et al. (2021). Machine learning models identify inhibitors of SARS-CoV2. Journal of Chemical Information and Modeling, 61( 9), 4224-4235. doi:10.1021/acs.jcim.1c00683
NLM
Oliveira VGF, Zin PPK, Puhl AC, Zorn KM, Foil DH, Lane TR, Hurst B, Tavella TA, Costa FTM, Lakshmanane P, Bernatchez J, Godoy AS de, Oliva G, Siqueira-Neto JL, Madrid PB, Ekins S. Machine learning models identify inhibitors of SARS-CoV2 [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 9): 4224-4235.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00683
Vancouver
Oliveira VGF, Zin PPK, Puhl AC, Zorn KM, Foil DH, Lane TR, Hurst B, Tavella TA, Costa FTM, Lakshmanane P, Bernatchez J, Godoy AS de, Oliva G, Siqueira-Neto JL, Madrid PB, Ekins S. Machine learning models identify inhibitors of SARS-CoV2 [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61( 9): 4224-4235.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c00683

Unidades USP

ReP

Filtros

Autores

Assuntos

Afiliação dos autores externos não normalizada