Machine Learning Classification Models for the Design of Novel Nitroimidazole Derivatives with Anti-Trichomonas vaginalis Activity.
- DOI
- 10.1021/acsomega.6c05649
- Published
- 2026 Aug 4
- Container
- ACS omega
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1021/acsomega.6c05649,
title = {Machine Learning Classification Models for the Design of Novel Nitroimidazole Derivatives with Anti-Trichomonas vaginalis Activity.},
author = {Veríssimo GC and Antoniassi AM and Rezende LG and Lamego VR and Dos Santos WT and de Paula ACC and Jaeger LH and Kronenberger T and de Oliveira RB and Maltarollo VG},
year = {2026},
journal = {ACS omega},
doi = {10.1021/acsomega.6c05649},
url = {https://doi.org/10.1021/acsomega.6c05649}
}RIS
TY - JOUR TI - Machine Learning Classification Models for the Design of Novel Nitroimidazole Derivatives with Anti-Trichomonas vaginalis Activity. AU - Veríssimo GC AU - Antoniassi AM AU - Rezende LG AU - Lamego VR AU - Dos Santos WT AU - de Paula ACC AU - Jaeger LH AU - Kronenberger T AU - de Oliveira RB AU - Maltarollo VG PY - 2026 JO - ACS omega DO - 10.1021/acsomega.6c05649 UR - https://doi.org/10.1021/acsomega.6c05649 ER -
APA
GC, V., AM, A., LG, R., VR, L., WT, D. S., ACC, D. P., LH, J., T, K., RB, D. O., & VG, M. (2026). Machine Learning Classification Models for the Design of Novel Nitroimidazole Derivatives with Anti-Trichomonas vaginalis Activity.. ACS omega. https://doi.org/10.1021/acsomega.6c05649
Source records
- pubmed · retrieved 2026-09-25T16:49:12.147Z