Machine learning models for the identification of natural products with anti-schistosomiasis activity (2025)
- Authors:
- Autor USP: HONORIO, KÁTHIA MARIA - EACH
- Unidade: EACH
- DOI: 10.21577/0103-5053.20250070
- Assunto: ESQUISTOSSOMOSE
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Journal Brazilian Chemical Society
- ISSN: 1678-4790
- Volume/Número/Paginação/Ano: v. 36, n. 8, p. 01-18, 2025
- Status:
- Artigo publicado em periódico de acesso aberto (Gold Open Access)
- Versão do Documento:
- Versão publicada (Published version)
- Acessar versão aberta:
-
ABNT
ANGELO, Rafaela Molina de et al. Machine learning models for the identification of natural products with anti-schistosomiasis activity. Journal Brazilian Chemical Society, v. 36, n. 8, p. 01-18, 2025Tradução . . Disponível em: http://dx.doi.org/10.21577/0103-5053.20250070. Acesso em: 06 maio 2026. -
APA
Angelo, R. M. de, Maltarollo, V. G., Lago, J. H. G., & Honorio, K. M. (2025). Machine learning models for the identification of natural products with anti-schistosomiasis activity. Journal Brazilian Chemical Society, 36( 8), 01-18. doi:10.21577/0103-5053.20250070 -
NLM
Angelo RM de, Maltarollo VG, Lago JHG, Honorio KM. Machine learning models for the identification of natural products with anti-schistosomiasis activity [Internet]. Journal Brazilian Chemical Society. 2025 ; 36( 8): 01-18.[citado 2026 maio 06 ] Available from: http://dx.doi.org/10.21577/0103-5053.20250070 -
Vancouver
Angelo RM de, Maltarollo VG, Lago JHG, Honorio KM. Machine learning models for the identification of natural products with anti-schistosomiasis activity [Internet]. Journal Brazilian Chemical Society. 2025 ; 36( 8): 01-18.[citado 2026 maio 06 ] Available from: http://dx.doi.org/10.21577/0103-5053.20250070 - Virtual screening and in vitro assays of novel hits as promising DPP-4 inhibitors
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