ReP USP - Resultado da busca

Artigo de periodico
Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika (2022)
Mottin, Melina ; Sousa, Bruna Katiele de Paula ; Mesquita, Nathalya Cristina de Moraes Roso; Oliveira, Ketllyn Irene Zagato de; Noske, Gabriela Dias; Sartori, Geraldo Rodrigues ; Albuquerque, Aline de Oliveira; Urbina, Fabio; Puhl, Ana C. ; Moreira Filho, José Teófilo; Souza, Guilherme Eduardo de ; Guido, Rafael Victorio Carvalho ; Muratov, Eugene ; Neves, Bruno Junior ; Silva, João Hermínio Martins da ; Clark, Alex E.; Siqueira Neto, Jair L. ; Perryman, Alexander L.; Oliva, Glaucius ; Ekins, Sean ; Andrade, Carolina Horta
Source: Journal of Chemical Information and Modeling. Unidade: IFSC
Subjects: ZIKA VÍRUS, PLANEJAMENTO DE FÁRMACOS, ANTIVIRAIS
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ABNT
MOTTIN, Melina et al. Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika. Journal of Chemical Information and Modeling, v. 62, n. 24, p. 6825-6843, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00596. Acesso em: 08 out. 2025.
APA
Mottin, M., Sousa, B. K. de P., Mesquita, N. C. de M. R., Oliveira, K. I. Z. de, Noske, G. D., Sartori, G. R., et al. (2022). Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika. Journal of Chemical Information and Modeling, 62( 24), 6825-6843. doi:10.1021/acs.jcim.2c00596
NLM
Mottin M, Sousa BK de P, Mesquita NC de MR, Oliveira KIZ de, Noske GD, Sartori GR, Albuquerque A de O, Urbina F, Puhl AC, Moreira Filho JT, Souza GE de, Guido RVC, Muratov E, Neves BJ, Silva JHM da, Clark AE, Siqueira Neto JL, Perryman AL, Oliva G, Ekins S, Andrade CH. Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6825-6843.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00596
Vancouver
Mottin M, Sousa BK de P, Mesquita NC de MR, Oliveira KIZ de, Noske GD, Sartori GR, Albuquerque A de O, Urbina F, Puhl AC, Moreira Filho JT, Souza GE de, Guido RVC, Muratov E, Neves BJ, Silva JHM da, Clark AE, Siqueira Neto JL, Perryman AL, Oliva G, Ekins S, Andrade CH. Discovery of new Zika protease and polymerase inhibitors through the open science collaboration Project OpenZika [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6825-6843.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00596
Artigo de periodico-carta/editorial
Computational chemistry in Asia [Editorial] (2022)
Wei, Guo-Wei; Soares, Thereza A. ; Wahab, Habibah A.; Wang, Renxiao
Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Subjects: PERIÓDICOS CIENTÍFICOS, QUÍMICA, QUÍMICA
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ABNT
WEI, Guo-Wei et al. Computational chemistry in Asia [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.2c01050. Acesso em: 08 out. 2025. , 2022
APA
Wei, G. -W., Soares, T. A., Wahab, H. A., & Wang, R. (2022). Computational chemistry in Asia [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.2c01050
NLM
Wei G-W, Soares TA, Wahab HA, Wang R. Computational chemistry in Asia [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 21): 5035-5037.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c01050
Vancouver
Wei G-W, Soares TA, Wahab HA, Wang R. Computational chemistry in Asia [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 21): 5035-5037.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c01050
Artigo de periodico
Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape (2022)
Santos, Denys ; Coutinho, Kaline Rabelo ; Silva, Thereza Amélia Soares da
Source: Journal of Chemical Information and Modeling. Unidades: IF, FFCLRP
Subjects: FÍSICO-QUÍMICA, FÍSICA MOLECULAR, SOFTWARE ESTATÍSTICO PARA MICROCOMPUTADORES, LIPÍDEOS DA MEMBRANA
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ABNT
SANTOS, Denys e COUTINHO, Kaline Rabelo e SILVA, Thereza Amélia Soares da. Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape. Journal of Chemical Information and Modeling, v. 62, n. 19, p. 4690-4701, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00673. Acesso em: 08 out. 2025.
APA
Santos, D., Coutinho, K. R., & Silva, T. A. S. da. (2022). Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape. Journal of Chemical Information and Modeling, 62( 19), 4690-4701. doi:10.1021/acs.jcim.2c00673
NLM
Santos D, Coutinho KR, Silva TAS da. Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4690-4701.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00673
Vancouver
Santos D, Coutinho KR, Silva TAS da. Surface Assessment via Grid Evaluation (SuAVE) for Every Surface Curvature and Cavity Shape [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4690-4701.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00673
Artigo de periodico
Bias amplification in gender, gender identity, and geographical affiliation (2022)
Cascella, Michele; Silva, Thereza Amélia Soares da
Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Subjects: PRECONCEITO, PESQUISA CIENTÍFICA
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ABNT
CASCELLA, Michele e SILVA, Thereza Amélia Soares da. Bias amplification in gender, gender identity, and geographical affiliation. Journal of Chemical Information and Modeling, v. 62, n. 24, p. 6297-6301, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00533. Acesso em: 08 out. 2025.
APA
Cascella, M., & Silva, T. A. S. da. (2022). Bias amplification in gender, gender identity, and geographical affiliation. Journal of Chemical Information and Modeling, 62( 24), 6297-6301. doi:10.1021/acs.jcim.2c00533
NLM
Cascella M, Silva TAS da. Bias amplification in gender, gender identity, and geographical affiliation [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6297-6301.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00533
Vancouver
Cascella M, Silva TAS da. Bias amplification in gender, gender identity, and geographical affiliation [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6297-6301.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00533
Artigo de periodico
Prioritizing virtual screening with interpretable interaction Fingerprints (2022)
Fassio, Alexandre Victor ; Shub, Laura ; Ponzoni, Luca ; McKinley, Jessica ; O’Meara, Matthew J. ; Ferreira, Rafaela S.; Keiser, Michael J. ; Minardi, Raquel C. de Melo
Source: Journal of Chemical Information and Modeling. Unidade: IFSC
Subjects: APRENDIZADO COMPUTACIONAL, FÁRMACOS (ESTUDO;DESENVOLVIMENTO)
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ABNT
FASSIO, Alexandre Victor et al. Prioritizing virtual screening with interpretable interaction Fingerprints. Journal of Chemical Information and Modeling, v. 62, n. 18, p. 4300-4318, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00695. Acesso em: 08 out. 2025.
APA
Fassio, A. V., Shub, L., Ponzoni, L., McKinley, J., O’Meara, M. J., Ferreira, R. S., et al. (2022). Prioritizing virtual screening with interpretable interaction Fingerprints. Journal of Chemical Information and Modeling, 62( 18), 4300-4318. doi:10.1021/acs.jcim.2c00695
NLM
Fassio AV, Shub L, Ponzoni L, McKinley J, O’Meara MJ, Ferreira RS, Keiser MJ, Minardi RC de M. Prioritizing virtual screening with interpretable interaction Fingerprints [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 18): 4300-4318.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00695
Vancouver
Fassio AV, Shub L, Ponzoni L, McKinley J, O’Meara MJ, Ferreira RS, Keiser MJ, Minardi RC de M. Prioritizing virtual screening with interpretable interaction Fingerprints [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 18): 4300-4318.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00695
Artigo de periodico
Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces (2022)
Santos, Alberto M. Dos; Oliveira, Amanda Ruslana Santana; Costa, Clauber H. S. da; Kenny, Peter W.; Montanari, Carlos Alberto ; Varela Júnior, Jaldyr de Jesus G.; Lameira, Jerônimo
Source: Journal of Chemical Information and Modeling. Unidade: IQSC
Subjects: AMINOÁCIDOS, MECÂNICA QUÂNTICA, ENERGIA
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ABNT
SANTOS, Alberto M. Dos et al. Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces. Journal of Chemical Information and Modeling, v. 62, p. 4083-4094, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00466. Acesso em: 08 out. 2025.
APA
Santos, A. M. D., Oliveira, A. R. S., Costa, C. H. S. da, Kenny, P. W., Montanari, C. A., Varela Júnior, J. de J. G., & Lameira, J. (2022). Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces. Journal of Chemical Information and Modeling, 62, 4083-4094. doi:10.1021/acs.jcim.2c00466
NLM
Santos AMD, Oliveira ARS, Costa CHS da, Kenny PW, Montanari CA, Varela Júnior J de JG, Lameira J. Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62 4083-4094.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00466
Vancouver
Santos AMD, Oliveira ARS, Costa CHS da, Kenny PW, Montanari CA, Varela Júnior J de JG, Lameira J. Assessment of Reversibility for Covalent Cysteine Protease Inhibitors Using Quantum Mechanics/Molecular Mechanics Free Energy Surfaces [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62 4083-4094.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00466
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
Source: Journal of Chemical Information and Modeling. Unidade: IQSC
Subjects: 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: 08 out. 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 out. 08 ] 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 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.1c01573
Artigo de periodico-carta/editorial
The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] (2022)
Soares, Thereza A. ; Alves, Ariane Ferreira Nunes; Mazzolari, Angelica; Ruggiu, Fiorella; Wei, Guo-Wei; Merz, Kenneth
Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Subjects: APRENDIZADO COMPUTACIONAL, MODELOS MATEMÁTICOS, ESTRUTURA MOLECULAR (QUÍMICA TEÓRICA)
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ABNT
SOARES, Thereza A. et al. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [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.2c01422. Acesso em: 08 out. 2025. , 2022
APA
Soares, T. A., Alves, A. F. N., Mazzolari, A., Ruggiu, F., Wei, G. -W., & Merz, K. (2022). The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [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.2c01422
NLM
Soares TA, Alves AFN, Mazzolari A, Ruggiu F, Wei G-W, Merz K. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 22): 5317-5320.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c01422
Vancouver
Soares TA, Alves AFN, Mazzolari A, Ruggiu F, Wei G-W, Merz K. The (Re)-evolution of Quantitative Structure–Activity Relationship (QSAR) studies propelled by the surge of machine learning methods [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 22): 5317-5320.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c01422
Artigo de periodico-carta/editorial
Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [Editorial] (2022)
Cournia, Zoe; Soares, Thereza A. ; Wahab, Habibah A.; Amaro, Rommie E.
Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Subjects: PERIÓDICOS CIENTÍFICOS, QUÍMICA TEÓRICA, CIÊNCIA
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ABNT
COURNIA, Zoe et al. Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [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.2c01543. Acesso em: 08 out. 2025. , 2022
APA
Cournia, Z., Soares, T. A., Wahab, H. A., & Amaro, R. E. (2022). Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [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.2c01543
NLM
Cournia Z, Soares TA, Wahab HA, Amaro RE. Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6287-6291.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c01543
Vancouver
Cournia Z, Soares TA, Wahab HA, Amaro RE. Celebrating diversity, equity, inclusion, and respect in computational and theoretical chemistry [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 24): 6287-6291.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c01543
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
Source: Journal of Chemical Information and Modeling. Unidade: IQSC
Subjects: 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: 08 out. 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 out. 08 ] 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 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00521
Artigo de periodico
Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining (2022)
Moraes, Alex S.; Pinheiro, Gabriel A.; Lourenço, Tuanan da Costa ; Lopes, Mauro C.; Quiles, Marcos G.; Dias, Luis G. ; Silva, Juarez Lopes Ferreira da
Source: Journal of Chemical Information and Modeling. Unidades: FFCLRP, IQSC
Subjects: ÍONS ELETRÔNICOS, ESTRUTURA ATÔMICA (QUÍMICA TEÓRICA), ENERGIA
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ABNT
MORAES, Alex S. et al. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining. Journal of Chemical Information and Modeling, v. 62, n. 19, p. 4702–4712, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00748. Acesso em: 08 out. 2025.
APA
Moraes, A. S., Pinheiro, G. A., Lourenço, T. da C., Lopes, M. C., Quiles, M. G., Dias, L. G., & Silva, J. L. F. da. (2022). Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining. Journal of Chemical Information and Modeling, 62( 19), 4702–4712. doi:10.1021/acs.jcim.2c00748
NLM
Moraes AS, Pinheiro GA, Lourenço T da C, Lopes MC, Quiles MG, Dias LG, Silva JLF da. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4702–4712.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00748
Vancouver
Moraes AS, Pinheiro GA, Lourenço T da C, Lopes MC, Quiles MG, Dias LG, Silva JLF da. Screening of the Role of the Chemical Structure in the Electrochemical Stability Window of Ionic Liquids: DFT Calculations Combined with Data Mining [Internet]. Journal of Chemical Information and Modeling. 2022 ; 62( 19): 4702–4712.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00748
Artigo de periodico
Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles (2022)
Mendonça, João Paulo A. de ; Calderan, Felipe V.; Lourenço, Tuanan da Costa ; Quiles, Marcos G.; Silva, Juarez Lopes Ferreira da
Source: Journal of Chemical Information and Modeling. Unidade: IQSC
Subjects: COMBUSTÍVEIS, COBRE, NANOCOMPOSITOS
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ABNT
MENDONÇA, João Paulo A. de et al. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles. Journal of Chemical Information and Modeling, v. 27, p. 5503-5512, 2022Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.2c00957. Acesso em: 08 out. 2025.
APA
Mendonça, J. P. A. de, Calderan, F. V., Lourenço, T. da C., Quiles, M. G., & Silva, J. L. F. da. (2022). Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles. Journal of Chemical Information and Modeling, 27, 5503-5512. doi:10.1021/acs.jcim.2c00957
NLM
Mendonça JPA de, Calderan FV, Lourenço T da C, Quiles MG, Silva JLF da. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles [Internet]. Journal of Chemical Information and Modeling. 2022 ; 27 5503-5512.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00957
Vancouver
Mendonça JPA de, Calderan FV, Lourenço T da C, Quiles MG, Silva JLF da. Theoretical Framework Based on Molecular Dynamics and Data Mining Analyses for the Study of Potential Energy Surfaces of FiniteSize Particles [Internet]. Journal of Chemical Information and Modeling. 2022 ; 27 5503-5512.[citado 2025 out. 08 ] Available from: https://doi.org/10.1021/acs.jcim.2c00957

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