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Artigo de periodico
The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling (2024)
Prati, Ronaldo C.; Rodrigues, Bruno S. M.; Aragão, Iberis; Silva, Thereza Amélia Soares da; Quiles, Marcos Gonçalves ; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidades: IQSC, FFCLRP
Assuntos: BIOENGENHARIA, BIOTECNOLOGIA, BIOLOGIA, MATERIAIS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
PRATI, Ronaldo C. et al. The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling. Journal of Chemical Information and Modeling, v. 64, n. 4, p. 1107–1111, 2024Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.3c02014. Acesso em: 17 nov. 2025.
APA
Prati, R. C., Rodrigues, B. S. M., Aragão, I., Silva, T. A. S. da, Quiles, M. G., & Silva, J. L. F. da. (2024). The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling. Journal of Chemical Information and Modeling, 64( 4), 1107–1111. doi:10.1021/acs.jcim.3c02014
NLM
Prati RC, Rodrigues BSM, Aragão I, Silva TAS da, Quiles MG, Silva JLF da. The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling [Internet]. Journal of Chemical Information and Modeling. 2024 ;64( 4): 1107–1111.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.3c02014
Vancouver
Prati RC, Rodrigues BSM, Aragão I, Silva TAS da, Quiles MG, Silva JLF da. The Impact of Interdisciplinary, Gender and Geographic Distributions on the Citation Patterns of the Journal of Chemical Information and Modeling [Internet]. Journal of Chemical Information and Modeling. 2024 ;64( 4): 1107–1111.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.3c02014
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 17 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. 17 ] 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. 17 ] 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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 17 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. 17 ] 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. 17 ] Available from: https://doi.org/10.1021/acs.jcim.2c00521
Artigo de periodico
Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters (2021)
Mucelini, Johnatan ; Quiles, Marcos Gonçalves ; Prati, Ronaldo Cristiano ; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assuntos: QUÍMICA QUÂNTICA, MINERAÇÃO DE DADOS, FRAMEWORKS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MUCELINI, Johnatan et al. Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters. Journal of Chemical Information and Modeling, v. 61, p. 1125-1135, 2021Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.0c01267. Acesso em: 17 nov. 2025.
APA
Mucelini, J., Quiles, M. G., Prati, R. C., & Silva, J. L. F. da. (2021). Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters. Journal of Chemical Information and Modeling, 61, 1125-1135. doi:10.1021/acs.jcim.0c01267
NLM
Mucelini J, Quiles MG, Prati RC, Silva JLF da. Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 1125-1135.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.0c01267
Vancouver
Mucelini J, Quiles MG, Prati RC, Silva JLF da. Correlation-based framework for extraction of insights from quantum chemistry databases: Applications for nanoclusters [Internet]. Journal of Chemical Information and Modeling. 2021 ; 61 1125-1135.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.0c01267
Artigo de periodico
Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters (2020)
Batista, Krys Elly de Araújo ; Restrepo, Vivianne k ; Soares, Marinalva Dias ; Quiles, Marcos Gonçalves ; Piotrowski, Maurício Jeomar ; Silva, Juarez Lopes Ferreira da
Fonte: Journal of Chemical Information and Modeling. Unidade: IQSC
Assunto: CLUSTERS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BATISTA, Krys Elly de Araújo et al. Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters. Journal of Chemical Information and Modeling, v. 60, p. 537-545, 2020Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.9b00792. Acesso em: 17 nov. 2025.
APA
Batista, K. E. de A., Restrepo, V. k, Soares, M. D., Quiles, M. G., Piotrowski, M. J., & Silva, J. L. F. da. (2020). Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters. Journal of Chemical Information and Modeling, 60, 537-545. doi:10.1021/acs.jcim.9b00792
NLM
Batista KE de A, Restrepo V k, Soares MD, Quiles MG, Piotrowski MJ, Silva JLF da. Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 537-545.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.9b00792
Vancouver
Batista KE de A, Restrepo V k, Soares MD, Quiles MG, Piotrowski MJ, Silva JLF da. Ab Initio Investigation of CO2 Adsorption on 13-Atom 4d Clusters [Internet]. Journal of Chemical Information and Modeling. 2020 ; 60 537-545.[citado 2025 nov. 17 ] Available from: https://doi.org/10.1021/acs.jcim.9b00792

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