Fuzz testing molecular representation using deep variational anomaly generation (2025)
Nogueira, Victor Henrique Rabesquine 
; Sharma, Rishabh; Guido, Rafael Victorio Carvalho ; Keiser, Michael James
Fonte: Journal of Chemical Information and Modeling. Unidade: IFSC
Assuntos: INTELIGÊNCIA ARTIFICIAL, MODELAGEM MOLECULAR, MOLÉCULA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
NOGUEIRA, Victor Henrique Rabesquine et al. Fuzz testing molecular representation using deep variational anomaly generation. Journal of Chemical Information and Modeling, v. 65, n. 4, p. 1911-1927 + supporting information, 2025Tradução . . Disponível em: https://doi.org/10.1021/acs.jcim.4c01876. Acesso em: 09 nov. 2025.APA
Nogueira, V. H. R., Sharma, R., Guido, R. V. C., & Keiser, M. J. (2025). Fuzz testing molecular representation using deep variational anomaly generation. Journal of Chemical Information and Modeling, 65( 4), 1911-1927 + supporting information. doi:10.1021/acs.jcim.4c01876NLM
Nogueira VHR, Sharma R, Guido RVC, Keiser MJ. Fuzz testing molecular representation using deep variational anomaly generation [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 4): 1911-1927 + supporting information.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.4c01876Vancouver
Nogueira VHR, Sharma R, Guido RVC, Keiser MJ. Fuzz testing molecular representation using deep variational anomaly generation [Internet]. Journal of Chemical Information and Modeling. 2025 ; 65( 4): 1911-1927 + supporting information.[citado 2025 nov. 09 ] Available from: https://doi.org/10.1021/acs.jcim.4c01876
