Filtros : "Journal of Biomolecular Structure and Dynamics" "Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)" Removido: "DOENÇAS NEGLIGENCIADAS" Limpar

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  • Source: Journal of Biomolecular Structure and Dynamics. Unidade: FCF

    Subjects: MACRÓFAGOS, SISTEMA IMUNE, LISOSSOMOS

    Acesso à fonteDOIHow to cite
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    • ABNT

      NASCIMENTO, Lucas Adriano do e FERREIRA, Glaucio Monteiro e FERREIRA, Elizabeth Igne. Exploring the conformational dynamics ofthe CRD4: a model for receptor lysosomalactivity shifts in search of 'sweet’ and ‘sour’states. Journal of Biomolecular Structure and Dynamics, v. 42, n. 12, p. 6448–6454, 2024Tradução . . Disponível em: https://doi.org/10.1080/07391102.2023.2235603. Acesso em: 24 nov. 2025.
    • APA

      Nascimento, L. A. do, Ferreira, G. M., & Ferreira, E. I. (2024). Exploring the conformational dynamics ofthe CRD4: a model for receptor lysosomalactivity shifts in search of 'sweet’ and ‘sour’states. Journal of Biomolecular Structure and Dynamics, 42( 12), 6448–6454. doi:10.1080/07391102.2023.2235603
    • NLM

      Nascimento LA do, Ferreira GM, Ferreira EI. Exploring the conformational dynamics ofthe CRD4: a model for receptor lysosomalactivity shifts in search of 'sweet’ and ‘sour’states [Internet]. Journal of Biomolecular Structure and Dynamics. 2024 ; 42( 12): 6448–6454.[citado 2025 nov. 24 ] Available from: https://doi.org/10.1080/07391102.2023.2235603
    • Vancouver

      Nascimento LA do, Ferreira GM, Ferreira EI. Exploring the conformational dynamics ofthe CRD4: a model for receptor lysosomalactivity shifts in search of 'sweet’ and ‘sour’states [Internet]. Journal of Biomolecular Structure and Dynamics. 2024 ; 42( 12): 6448–6454.[citado 2025 nov. 24 ] Available from: https://doi.org/10.1080/07391102.2023.2235603
  • Source: Journal of Biomolecular Structure and Dynamics. Unidade: FCF

    Subjects: APRENDIZADO COMPUTACIONAL, RELAÇÕES QUANTITATIVAS ENTRE ESTRUTURA QUÍMICA E ATIVIDADE BIOLÓGICA

    Acesso à fonteDOIHow to cite
    A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
    • ABNT

      SOUSA, Gustavo Henrique Marques et al. Machine learning methods applied for the prediction of biological activities of triple reuptake inhibitors. Journal of Biomolecular Structure and Dynamics, v. 41, n. 20, p. 10277-10286, 2023Tradução . . Disponível em: https://doi.org/10.1080/07391102.2022.2154269. Acesso em: 24 nov. 2025.
    • APA

      Sousa, G. H. M., Gomes, R. A., Oliveira, E. O. de, & Trossini, G. H. G. (2023). Machine learning methods applied for the prediction of biological activities of triple reuptake inhibitors. Journal of Biomolecular Structure and Dynamics, 41( 20), 10277-10286. doi:10.1080/07391102.2022.2154269
    • NLM

      Sousa GHM, Gomes RA, Oliveira EO de, Trossini GHG. Machine learning methods applied for the prediction of biological activities of triple reuptake inhibitors [Internet]. Journal of Biomolecular Structure and Dynamics. 2023 ; 41( 20): 10277-10286.[citado 2025 nov. 24 ] Available from: https://doi.org/10.1080/07391102.2022.2154269
    • Vancouver

      Sousa GHM, Gomes RA, Oliveira EO de, Trossini GHG. Machine learning methods applied for the prediction of biological activities of triple reuptake inhibitors [Internet]. Journal of Biomolecular Structure and Dynamics. 2023 ; 41( 20): 10277-10286.[citado 2025 nov. 24 ] Available from: https://doi.org/10.1080/07391102.2022.2154269

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