ReP USP - Resultado da busca

Artigo de periodico
Inhibition of 3-Hydroxykynurenine transaminase from Aedes aegypti and Anopheles gambiae: a mosquito-specific target to combat the transmission of arboviruses (2023)
Maciel, Larissa Gonçalves ; Ferraz, Matheus Vitor Ferreira ; Oliveira, Andrew Albert de ; Lins, Roberto Dias ; Anjos, Janaína Versiani; Guido, Rafael Victorio Carvalho ; Soares, Thereza Amélia
Source: ACS Bio and Med Chem Au. Unidades: IFSC, FFCLRP, FMRP
Subjects: AEDES, LARVICIDAS, ARBOVÍRUS, EXPRESSÃO GÊNICA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
MACIEL, Larissa Gonçalves et al. Inhibition of 3-Hydroxykynurenine transaminase from Aedes aegypti and Anopheles gambiae: a mosquito-specific target to combat the transmission of arboviruses. ACS Bio and Med Chem Au, v. 3, n. 2, p. 211-222 + supporting information, 2023Tradução . . Disponível em: https://doi.org/10.1021/acsbiomedchemau.2c00080. Acesso em: 03 ago. 2024.
APA
Maciel, L. G., Ferraz, M. V. F., Oliveira, A. A. de, Lins, R. D., Anjos, J. V., Guido, R. V. C., & Soares, T. A. (2023). Inhibition of 3-Hydroxykynurenine transaminase from Aedes aegypti and Anopheles gambiae: a mosquito-specific target to combat the transmission of arboviruses. ACS Bio and Med Chem Au, 3( 2), 211-222 + supporting information. doi:10.1021/acsbiomedchemau.2c00080
NLM
Maciel LG, Ferraz MVF, Oliveira AA de, Lins RD, Anjos JV, Guido RVC, Soares TA. Inhibition of 3-Hydroxykynurenine transaminase from Aedes aegypti and Anopheles gambiae: a mosquito-specific target to combat the transmission of arboviruses [Internet]. ACS Bio and Med Chem Au. 2023 ; 3( 2): 211-222 + supporting information.[citado 2024 ago. 03 ] Available from: https://doi.org/10.1021/acsbiomedchemau.2c00080
Vancouver
Maciel LG, Ferraz MVF, Oliveira AA de, Lins RD, Anjos JV, Guido RVC, Soares TA. Inhibition of 3-Hydroxykynurenine transaminase from Aedes aegypti and Anopheles gambiae: a mosquito-specific target to combat the transmission of arboviruses [Internet]. ACS Bio and Med Chem Au. 2023 ; 3( 2): 211-222 + supporting information.[citado 2024 ago. 03 ] Available from: https://doi.org/10.1021/acsbiomedchemau.2c00080
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 03 ago. 2024.
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 2024 ago. 03 ] 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 2024 ago. 03 ] Available from: https://doi.org/10.1021/acs.jcim.2c00533
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
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 03 ago. 2024.
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 2024 ago. 03 ] 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 2024 ago. 03 ] Available from: https://doi.org/10.1021/acs.jcim.2c00673
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)
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
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: 03 ago. 2024. , 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 2024 ago. 03 ] 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 2024 ago. 03 ] Available from: https://doi.org/10.1021/acs.jcim.2c01422

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