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Filtros : " GRU999" "University of California San Diego - UCSD - La Jolla - CA - USA" Removido: "IFSC-FCI" Limpar

Filtros

USP affiliated authors
- oliva, glaucius (~2)
- godoy, andre schützer de (~1)
- mesquita, nathalya cristina de moraes roso (~1)
- oliveira, victor gawriljuk ferraro (~1)
Date published
- 2021 (~1)
- 2020 (~1)
Subjects
- antivirais (1)
- aprendizado computacional (1)
- coronavirus (1)
- covid-19 (1)
- enzimas (1)

Language
- inglês (~2)
Source title
- anais (~1)
- journal of chemical information and modeling (~1)
Publisher
- galoá (~1)
Conference titles
- reunião anual virtual da sociedade brasileira de química - rasbq (~1)
Countries/Territories
- brasil (~1)
- estados unidos (~1)
Grupo de pesquisa
- gru999 (~2)
- gru016 (~1)
- gru015 (~1)
- gru016 (~1)
Funding Agencies
- fundação de amparo à pesquisa do estado de são paulo (fapesp) (2)
- conselho nacional de desenvolvimento científico e tecnológico (cnpq) (1)
- coordenação de aperfeiçoamento de pessoal de nível superior (capes) (1)
- financiado pela fapeg (1)
- financiado pela ibm (1)

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
Source: Journal of Chemical Information and Modeling. Unidade: IFSC
Subjects: 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: 02 jun. 2024.
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 2024 jun. 02 ] 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 2024 jun. 02 ] Available from: https://doi.org/10.1021/acs.jcim.1c00683
Trabalho de evento-resumo
Discovery of novel Zika virus NS3 protein inhibitors through the integration of docking, machine learning models and experimental evaluation (2020)
Sousa, Bruna K. P.; Mottin, Melina; Bernatchez, Jean; Mesquita, Nathalya Cristina de Moraes Roso; Zhu, Zhe; Rich, Jeremy; Clark, Alex E.; Zorn, Kimberley M.; Foil, Daniel; Sartori, Geraldo R.; Albuquerque, Aline O.; Silva, João H. M. da; Neves, Bruno J.; Muratov, Eugene; Oliva, Glaucius ; Siqueira Neto, Jair; Ekins, Sean; Andrade, Carolina Horta
Source: Anais. Conference titles: Reunião Anual Virtual da Sociedade Brasileira de Química - RASBQ. Unidade: IFSC
Subjects: ZIKA VÍRUS, PRODUTOS NATURAIS, ENZIMAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
SOUSA, Bruna K. P. et al. Discovery of novel Zika virus NS3 protein inhibitors through the integration of docking, machine learning models and experimental evaluation. 2020, Anais.. Campinas: Galoá, 2020. Disponível em: https://proceedings.science/rasbq-2020/papers/discovery-of-novel-zika-virus-ns3-protein-inhibitors-through-the-integration-of-docking--machine-learning-models-and-exp. Acesso em: 02 jun. 2024.
APA
Sousa, B. K. P., Mottin, M., Bernatchez, J., Mesquita, N. C. de M. R., Zhu, Z., Rich, J., et al. (2020). Discovery of novel Zika virus NS3 protein inhibitors through the integration of docking, machine learning models and experimental evaluation. In Anais. Campinas: Galoá. Recuperado de https://proceedings.science/rasbq-2020/papers/discovery-of-novel-zika-virus-ns3-protein-inhibitors-through-the-integration-of-docking--machine-learning-models-and-exp
NLM
Sousa BKP, Mottin M, Bernatchez J, Mesquita NC de MR, Zhu Z, Rich J, Clark AE, Zorn KM, Foil D, Sartori GR, Albuquerque AO, Silva JHM da, Neves BJ, Muratov E, Oliva G, Siqueira Neto J, Ekins S, Andrade CH. Discovery of novel Zika virus NS3 protein inhibitors through the integration of docking, machine learning models and experimental evaluation [Internet]. Anais. 2020 ;[citado 2024 jun. 02 ] Available from: https://proceedings.science/rasbq-2020/papers/discovery-of-novel-zika-virus-ns3-protein-inhibitors-through-the-integration-of-docking--machine-learning-models-and-exp
Vancouver
Sousa BKP, Mottin M, Bernatchez J, Mesquita NC de MR, Zhu Z, Rich J, Clark AE, Zorn KM, Foil D, Sartori GR, Albuquerque AO, Silva JHM da, Neves BJ, Muratov E, Oliva G, Siqueira Neto J, Ekins S, Andrade CH. Discovery of novel Zika virus NS3 protein inhibitors through the integration of docking, machine learning models and experimental evaluation [Internet]. Anais. 2020 ;[citado 2024 jun. 02 ] Available from: https://proceedings.science/rasbq-2020/papers/discovery-of-novel-zika-virus-ns3-protein-inhibitors-through-the-integration-of-docking--machine-learning-models-and-exp

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