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Filtros : "Journal of Chemical Information and Modeling" "MOLÉCULA" Limpar

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1 - 6 (6 registros)

  • Artigo de periodico

    Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1 (2025)

    Camilo, Sofia Rodrigues Guedes; Arantes, Guilherme Menegon

    Fonte: Journal of Chemical Information and Modeling. Unidade: IQ

    Assuntos: BIOQUÍMICA INORGÂNICA, MOLÉCULA, PEPTÍDEOS, PROTEÍNAS

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    • ABNT

      CAMILO, Sofia Rodrigues Guedes e ARANTES, Guilherme Menegon. Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1. Journal of Chemical Information and Modeling, v. 65, n. 12, p. 6184-6197, 2025Tradução . . Disponível em: https://dx.doi.org/10.1021/acs.jcim.5c00655. Acesso em: 09 nov. 2025.

    • APA

      Camilo, S. R. G., & Arantes, G. M. (2025). Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1. Journal of Chemical Information and Modeling, 65( 12), 6184-6197. doi:10.1021/acs.jcim.5c00655

    • NLM

      Camilo SRG, Arantes GM. Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1 [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 12): 6184-6197.[citado 2025 nov. 09 ] Available from: https://dx.doi.org/10.1021/acs.jcim.5c00655

    • Vancouver

      Camilo SRG, Arantes GM. Flexibility and hydration of the Qo site determine multiple pathways for proton transfer in cytochrome bc1 [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 12): 6184-6197.[citado 2025 nov. 09 ] Available from: https://dx.doi.org/10.1021/acs.jcim.5c00655

  • Artigo de periodico

    Fuzz testing molecular representation using deep variational anomaly generation (2025)

    Nogueira, Victor Henrique Rabesquine ; Sharma, Rishabh; Guido, Rafael Victorio Carvalho ; Keiser, Michael James

    Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC

    Assuntos: INTELIGÊNCIA ARTIFICIAL, MODELAGEM MOLECULAR, MOLÉCULA

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    • ABNT

      NOGUEIRA, Victor Henrique Rabesquine et al. Fuzz testing molecular representation using deep variational anomaly generation. Journal of Chemical Information and Modeling, v. 65, n. 4, p. 1911-1927 + supporting information, 2025Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.4c01876. Acesso em: 09 nov. 2025.

    • APA

      Nogueira, V. H. R., Sharma, R., Guido, R. V. C., & Keiser, M. J. (2025). Fuzz testing molecular representation using deep variational anomaly generation. Journal of Chemical Information and Modeling, 65( 4), 1911-1927 + supporting information. doi:10.1021/acs.jcim.4c01876

    • NLM

      Nogueira VHR, Sharma R, Guido RVC, Keiser MJ. Fuzz testing molecular representation using deep variational anomaly generation [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 4): 1911-1927 + supporting information.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.4c01876

    • Vancouver

      Nogueira VHR, Sharma R, Guido RVC, Keiser MJ. Fuzz testing molecular representation using deep variational anomaly generation [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 4): 1911-1927 + supporting information.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.4c01876

  • Artigo de periodico-carta/editorial

    Guidelines for reporting molecular dynamics simulations in JCIM publications. [Editorial] (2023)

    Soares, Thereza A. ; Cournia, Zoe; Naidoo, Kevin J.; Amaro, Rommie E.; Wahab, Habibah A.; Merz, Kenneth

    Fonte: Journal of Chemical Information and Modeling. Unidade: FFCLRP

    Assuntos: QUÍMICA TEÓRICA, MOLÉCULA, PESQUISA CIENTÍFICA

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    • ABNT

      SOARES, Thereza A. et al. Guidelines for reporting molecular dynamics simulations in JCIM publications. [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. Disponível em: https://doi.org/10.1021/acs.jcim.3c00599. Acesso em: 09 nov. 2025. , 2023

    • APA

      Soares, T. A., Cournia, Z., Naidoo, K. J., Amaro, R. E., Wahab, H. A., & Merz, K. (2023). Guidelines for reporting molecular dynamics simulations in JCIM publications. [Editorial]. Journal of Chemical Information and Modeling. Washington: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo. doi:10.1021/acs.jcim.3c00599

    • NLM

      Soares TA, Cournia Z, Naidoo KJ, Amaro RE, Wahab HA, Merz K. Guidelines for reporting molecular dynamics simulations in JCIM publications. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63( 11): 3227-3229.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.3c00599

    • Vancouver

      Soares TA, Cournia Z, Naidoo KJ, Amaro RE, Wahab HA, Merz K. Guidelines for reporting molecular dynamics simulations in JCIM publications. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2023 ; 63( 11): 3227-3229.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.3c00599

  • Artigo de periodico

    Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder (2022)

    Oliveira, Andre F ; Silva, Juarez Lopes Ferreira da ; Quiles, Marcos Gonçalves

    Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC

    Assuntos: ENERGIA, MOLÉCULA

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    • ABNT

      OLIVEIRA, Andre F e SILVA, Juarez Lopes Ferreira da e QUILES, Marcos Gonçalves. Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder. Journal of Chemical Information and Modeling, v. 62, p. 817−828, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.1c01573. Acesso em: 09 nov. 2025.

    • APA

      Oliveira, A. F., Silva, J. L. F. da, & Quiles, M. G. (2022). Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder. Journal of Chemical Information and Modeling, 62, 817−828. doi:10.1021/acs.jcim.1c01573

    • NLM

      Oliveira AF, Silva JLF da, Quiles MG. Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62 817−828.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.1c01573

    • Vancouver

      Oliveira AF, Silva JLF da, Quiles MG. Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62 817−828.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.1c01573

  • Artigo de periodico

    SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning (2022)

    Pinheiro, Gabriel A.; Silva, Juarez Lopes Ferreira da ; Quiles, Marcos Gonçalves

    Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC

    Assuntos: MODELAGEM MOLECULAR, MOLÉCULA, QUÍMICA TEÓRICA

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    • ABNT

      PINHEIRO, Gabriel A. e SILVA, Juarez Lopes Ferreira da e QUILES, Marcos Gonçalves. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning. Journal of Chemical Information and Modeling, v. 62, n. 17, p. 3948–3960, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00521. Acesso em: 09 nov. 2025.

    • APA

      Pinheiro, G. A., Silva, J. L. F. da, & Quiles, M. G. (2022). SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning. Journal of Chemical Information and Modeling, 62( 17), 3948–3960. doi:10.1021/acs.jcim.2c00521

    • NLM

      Pinheiro GA, Silva JLF da, Quiles MG. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 17): 3948–3960.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.2c00521

    • Vancouver

      Pinheiro GA, Silva JLF da, Quiles MG. SMICLR: Contrastive Learning on Multiple Molecular Representations for Semisupervised and Unsupervised Representation Learning [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 17): 3948–3960.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.2c00521

  • Artigo de periodico

    Self-assembly of phosphocholine derivatives using the ELBA coarse-grained model: micelles, bicelles, and reverse micelles (2020)

    Souza, Rafael Maglia de ; Ratochinski, Rafael Henrique; Karttunen, Mikko; Dias, Luis Gustavo

    Fonte: Journal of Chemical Information and Modeling. Unidade: FFCLRP

    Assuntos: LIPÍDEOS, ELETROSTÁTICA, MOLÉCULA, QUÍMICA

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    • ABNT

      SOUZA, Rafael Maglia de et al. Self-assembly of phosphocholine derivatives using the ELBA coarse-grained model: micelles, bicelles, and reverse micelles. Journal of Chemical Information and Modeling, v. 60, n. 2, p. 522-536, 2020Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.9b00790. Acesso em: 09 nov. 2025.

    • APA

      Souza, R. M. de, Ratochinski, R. H., Karttunen, M., & Dias, L. G. (2020). Self-assembly of phosphocholine derivatives using the ELBA coarse-grained model: micelles, bicelles, and reverse micelles. Journal of Chemical Information and Modeling, 60( 2), 522-536. doi:10.1021/acs.jcim.9b00790

    • NLM

      Souza RM de, Ratochinski RH, Karttunen M, Dias LG. Self-assembly of phosphocholine derivatives using the ELBA coarse-grained model: micelles, bicelles, and reverse micelles [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 2): 522-536.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.9b00790

    • Vancouver

      Souza RM de, Ratochinski RH, Karttunen M, Dias LG. Self-assembly of phosphocholine derivatives using the ELBA coarse-grained model: micelles, bicelles, and reverse micelles [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60( 2): 522-536.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.9b00790
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