Molecular Property Prediction and Molecular Design Using a Supervised Grammar Variational Autoencoder (2022)
- Authors:
- Autor USP: SILVA, JUAREZ LOPES FERREIRA DA - IQSC
- Unidade: IQSC
- DOI: 10.1021/acs.jcim.1c01573
- Subjects: ENERGIA; MOLÉCULA
- Keywords: Molecular properties; Algorithms; Molecular modeling
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Washington
- Date published: 2022
- Source:
- Título: Journal of Chemical Information and Modeling
- ISSN: 1549-9596
- Volume/Número/Paginação/Ano: v. 62, p. 817−828, 2022
- Status:
- Nenhuma versão em acesso aberto identificada
-
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: 11 abr. 2026. -
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 2026 abr. 11 ] 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 2026 abr. 11 ] Available from: https://doi.org/10.1021/acs.jcim.1c01573 - Hybrid density functional study of small Rhn (n = 2−15) clusters
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