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Artigo de periodico
Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches (2024)
Barbosa, Henrique ; Espinoza, Gabriel Zarzana; Amaral, Maiara; Levatti, Erica Valadares de Castro ; Abiuzi, Mariana Babberg ; Veríssimo, Gabriel Corrêa ; Fernandes, Philipe Oliveira ; Maltarollo, Vinícius Gonçalves ; Tempone, Andre Gustavo ; Honorio, Kathia Maria ; Lago, João Henrique Ghilardi
Source: Journal of Chemical Information and Modeling. Unidade: EACH
Assunto: DOENÇA DE CHAGAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BARBOSA, Henrique et al. Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches. Journal of Chemical Information and Modeling, v. 64, p. 2565−2576, 2024Tradução . . Disponível em: http://dx.doi.org/10.1021/acs.jcim.3c01410. Acesso em: 19 nov. 2025.
APA
Barbosa, H., Espinoza, G. Z., Amaral, M., Levatti, E. V. de C., Abiuzi, M. B., Veríssimo, G. C., et al. (2024). Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches. Journal of Chemical Information and Modeling, 64, 2565−2576. doi:10.1021/acs.jcim.3c01410
NLM
Barbosa H, Espinoza GZ, Amaral M, Levatti EV de C, Abiuzi MB, Veríssimo GC, Fernandes PO, Maltarollo VG, Tempone AG, Honorio KM, Lago JHG. Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64 2565−2576.[citado 2025 nov. 19 ] Available from: http://dx.doi.org/10.1021/acs.jcim.3c01410
Vancouver
Barbosa H, Espinoza GZ, Amaral M, Levatti EV de C, Abiuzi MB, Veríssimo GC, Fernandes PO, Maltarollo VG, Tempone AG, Honorio KM, Lago JHG. Andrographolide: a diterpenoid from cymbopogon schoenanthus identified as a new hit compound against trypanosoma cruzi using machine learning and experimental approaches [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64 2565−2576.[citado 2025 nov. 19 ] Available from: http://dx.doi.org/10.1021/acs.jcim.3c01410
Artigo de periodico-carta/editorial
Machine Learning in Materials Science. [Editorial] (2024)
Merz, Kenneth M; Choong, Yee Siew; Cournia, Zoe; Isayev, Olexandr; Soares, Thereza Amélia ; Wei, Guo-Wei; Zhu, Feng
Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Subjects: ALGORITMOS, APRENDIZADO COMPUTACIONAL, BIOMATERIAIS
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ABNT
MERZ, Kenneth M et al. Machine Learning in Materials Science. [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.4c00727. Acesso em: 19 nov. 2025. , 2024
APA
Merz, K. M., Choong, Y. S., Cournia, Z., Isayev, O., Soares, T. A., Wei, G. -W., & Zhu, F. (2024). Machine Learning in Materials Science. [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.4c00727
NLM
Merz KM, Choong YS, Cournia Z, Isayev O, Soares TA, Wei G-W, Zhu F. Machine Learning in Materials Science. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 10): 3959-3960.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.4c00727
Vancouver
Merz KM, Choong YS, Cournia Z, Isayev O, Soares TA, Wei G-W, Zhu F. Machine Learning in Materials Science. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 10): 3959-3960.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.4c00727
Artigo de periodico
Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights (2024)
González, José E.; Besse, Rafael; Lima, Matheus P.; Silva, Juarez Lopes Ferreira da
Source: Journal of Chemical Information and Modeling. Unidade: IQSC
Subjects: ENERGIA, QUÍMICA TEÓRICA
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ABNT
GONZÁLEZ, José E. et al. Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights. Journal of Chemical Information and Modeling, v. 64, n. 4, p. 1306–1318, 2024Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.3c01895. Acesso em: 19 nov. 2025.
APA
González, J. E., Besse, R., Lima, M. P., & Silva, J. L. F. da. (2024). Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights. Journal of Chemical Information and Modeling, 64( 4), 1306–1318. doi:10.1021/acs.jcim.3c01895
NLM
González JE, Besse R, Lima MP, Silva JLF da. Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights [Internet]. Journal of Chemical Information and Modeling. 2024 ;64( 4): 1306–1318.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.3c01895
Vancouver
González JE, Besse R, Lima MP, Silva JLF da. Decoding Van der Waals Impact on Chirality Transfer in Perovskite Structures: Density Functional Theory Insights [Internet]. Journal of Chemical Information and Modeling. 2024 ;64( 4): 1306–1318.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.3c01895
Artigo de periodico-carta/editorial
Enhancing coarse-grained models through machine learning. [Editorial] (2024)
Karmakar, Tarak; Soares, Thereza Amélia ; Merz Jr, Kenneth M
Source: Journal of Chemical Information and Modeling. Unidade: FFCLRP
Subjects: APRENDIZADO COMPUTACIONAL, SIMULAÇÃO, MODELAGEM MOLECULAR, NANOPARTÍCULAS
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
KARMAKAR, Tarak e SOARES, Thereza Amélia e MERZ JR, Kenneth M. Enhancing coarse-grained models through machine learning. [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.4c00537. Acesso em: 19 nov. 2025. , 2024
APA
Karmakar, T., Soares, T. A., & Merz Jr, K. M. (2024). Enhancing coarse-grained models through machine learning. [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.4c00537
NLM
Karmakar T, Soares TA, Merz Jr KM. Enhancing coarse-grained models through machine learning. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 8): 2931-2932.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.4c00537
Vancouver
Karmakar T, Soares TA, Merz Jr KM. Enhancing coarse-grained models through machine learning. [Editorial] [Internet]. Journal of Chemical Information and Modeling. 2024 ; 64( 8): 2931-2932.[citado 2025 nov. 19 ] Available from: https://doi.org/10.1021/acs.jcim.4c00537
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
Source: Journal of Chemical Information and Modeling. Unidades: IQSC, FFCLRP
Subjects: 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: 19 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. 19 ] 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. 19 ] Available from: https://doi.org/10.1021/acs.jcim.3c02014

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