Time evolution of bacterial resistance observed with principal component analysis (2025)
- Authors:
- USP affiliated authors: BLANCO, KATE CRISTINA - IFSC ; BAGNATO, VANDERLEI SALVADOR - IFSC ; PATIÑO, CLAUDIA PATRICIA BARRERA - IFSC ; SOARES, JENNIFER MACHADO - IFSC
- Unidade: IFSC
- DOI: 10.3390/antibiotics14070729
- Subjects: ANTIBIÓTICOS; TERAPIA FOTODINÂMICA; RESISTÊNCIA MICROBIANA ÀS DROGAS; STAPHYLOCOCCUS; APRENDIZADO COMPUTACIONAL
- Keywords: Antibiotic-resistant bacteria; Staphylococcus aureus; Fourier transformation infrared; Minimum inhibitory concentration; Machine learning algorithms
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Antibiotics
- ISSN: 2079-6382
- Volume/Número/Paginação/Ano: v. 14, n. 7, p. 729-1-729-20 + supplementary material, July 2025
- Status:
- Artigo publicado em periódico de acesso aberto (Gold Open Access)
- Versão do Documento:
- Versão publicada (Published version)
- Acessar versão aberta:
-
ABNT
PATIÑO, Claudia Patricia Barrera et al. Time evolution of bacterial resistance observed with principal component analysis. Antibiotics, v. 14, n. 7, p. 729-1-729-20 + supplementary material, 2025Tradução . . Disponível em: https://doi.org/10.3390/antibiotics14070729. Acesso em: 07 abr. 2026. -
APA
Patiño, C. P. B., Bonner, M., Borsatto, A. R., Soares, J. M., Blanco, K. C., & Bagnato, V. S. (2025). Time evolution of bacterial resistance observed with principal component analysis. Antibiotics, 14( 7), 729-1-729-20 + supplementary material. doi:10.3390/antibiotics14070729 -
NLM
Patiño CPB, Bonner M, Borsatto AR, Soares JM, Blanco KC, Bagnato VS. Time evolution of bacterial resistance observed with principal component analysis [Internet]. Antibiotics. 2025 ; 14( 7): 729-1-729-20 + supplementary material.[citado 2026 abr. 07 ] Available from: https://doi.org/10.3390/antibiotics14070729 -
Vancouver
Patiño CPB, Bonner M, Borsatto AR, Soares JM, Blanco KC, Bagnato VS. Time evolution of bacterial resistance observed with principal component analysis [Internet]. Antibiotics. 2025 ; 14( 7): 729-1-729-20 + supplementary material.[citado 2026 abr. 07 ] Available from: https://doi.org/10.3390/antibiotics14070729 - Machine learning in FTIR spectrum for the identification of antibiotic resistance: a demonstration with different species of microorganisms
- FTIR-derived feature insights for predicting time-dependent antibiotic resistance progression
- Identification of antibiotic resistance in FTIR spectra of bacteria with machine learning algorithms
- Implementation of machine learning study in Staphylococcus aureus’s FTIR spectra to antibiotic resistance identification
- Identification of antibiotic resistance susceptibility in different species of microorganisms implementing machine learning
- Spectroscopic identification of bacteria resistance to antibiotics by means of absorption of specific biochemical groups and special machine learning algorithm
- Combinação de antibiótico com inativação fotodinâmica para o tratamento de infecções bacterianas
- Combination of antifungals with photodynamic inactivation to reduce fungal resistance
- Challenging resistance: photodynamic strategies against multi-resistant bacteria
- Exploring photodynamic inactivation to combat antimicrobial resistance (Presentation + Paper)
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