Use of machine learning approaches for novel drug discovery (2016)
- Authors:
- USP affiliated authors: TROSSINI, GUSTAVO HENRIQUE GOULART - FCF ; HONORIO, KÁTHIA MARIA - EACH
- Unidades: FCF; EACH
- DOI: 10.1517/17460441.2016.1146250
- Subjects: HISTOPLASMA; LEUCÓCITOS
- Language: Inglês
- Imprenta:
- Source:
- Título: Expert Opinion on Drug Discovery
- ISSN: 1746-0441
- Volume/Número/Paginação/Ano: v. 11, n. 3, p. 225-239, 2016
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
LIMA, Angélica Nakagawa et al. Use of machine learning approaches for novel drug discovery. Expert Opinion on Drug Discovery, v. 11, n. 3, p. 225-239, 2016Tradução . . Disponível em: https://doi.org/10.1517/17460441.2016.1146250. Acesso em: 11 maio 2025. -
APA
Lima, A. N., Philot, E. A., Trossini, G. H. G., Scott, L. P. B., Maltarollo, V. G., & Honório, K. M. (2016). Use of machine learning approaches for novel drug discovery. Expert Opinion on Drug Discovery, 11( 3), 225-239. doi:10.1517/17460441.2016.1146250 -
NLM
Lima AN, Philot EA, Trossini GHG, Scott LPB, Maltarollo VG, Honório KM. Use of machine learning approaches for novel drug discovery [Internet]. Expert Opinion on Drug Discovery. 2016 ; 11( 3): 225-239.[citado 2025 maio 11 ] Available from: https://doi.org/10.1517/17460441.2016.1146250 -
Vancouver
Lima AN, Philot EA, Trossini GHG, Scott LPB, Maltarollo VG, Honório KM. Use of machine learning approaches for novel drug discovery [Internet]. Expert Opinion on Drug Discovery. 2016 ; 11( 3): 225-239.[citado 2025 maio 11 ] Available from: https://doi.org/10.1517/17460441.2016.1146250 - Simulação do espectro de absorção UV do filtro solar p-metoxicinamato de etilexila empregando métodos teóricos (TD-DFT)
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Informações sobre o DOI: 10.1517/17460441.2016.1146250 (Fonte: oaDOI API)
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