Cargando…
Heterologous Machine Learning for the Identification of Antimicrobial Activity in Human-Targeted Drugs
The emergence of microbes resistant to common antibiotics represent a current treat to human health. It has been recently recognized that non-antibiotic labeled drugs may promote antibiotic-resistance mechanisms in the human microbiome by presenting a secondary antibiotic activity; hence, the develo...
Autores principales: | Nava Lara, Rodrigo A., Aguilera-Mendoza, Longendri, Brizuela, Carlos A., Peña, Antonio, Del Rio, Gabriel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479866/ https://www.ncbi.nlm.nih.gov/pubmed/30935109 http://dx.doi.org/10.3390/molecules24071258 |
Ejemplares similares
-
Relevant Features of Polypharmacologic Human-Target Antimicrobials Discovered by Machine-Learning Techniques
por: Nava Lara, Rodrigo A., et al.
Publicado: (2020) -
Optimal selection of molecular descriptors for antimicrobial peptides classification: an evolutionary feature weighting approach
por: Beltran, Jesus A., et al.
Publicado: (2018) -
Systematic Identification of Machine-Learning Models Aimed to Classify Critical Residues for Protein Function from Protein Structure
por: Corral-Corral, Ricardo, et al.
Publicado: (2017) -
Antimicrobial peptides with cell-penetrating activity as prophylactic and treatment drugs
por: del Rio, Gabriel, et al.
Publicado: (2022) -
Automatic construction of molecular similarity networks for visual graph mining in chemical space of bioactive peptides: an unsupervised learning approach
por: Aguilera-Mendoza, Longendri, et al.
Publicado: (2020)