Cargando…
Predictive classifier models built from natural products with antimalarial bioactivity using machine learning approach
In view of the vast number of natural products with potential antiplasmodial bioactivity and cost of conducting antiplasmodial bioactivity assays, it may be judicious to learn from previous antiplasmodial bioassays and predict bioactivity of these natural products before experimental bioassays. This...
Autores principales: | Egieyeh, Samuel, Syce, James, Malan, Sarel F., Christoffels, Alan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6161899/ https://www.ncbi.nlm.nih.gov/pubmed/30265702 http://dx.doi.org/10.1371/journal.pone.0204644 |
Ejemplares similares
-
Exploration of Scaffolds from Natural Products with Antiplasmodial Activities, Currently Registered Antimalarial Drugs and Public Malarial Screen Data
por: Egieyeh, Samuel, et al.
Publicado: (2016) -
Prioritization of anti-malarial hits from nature: chemo-informatic profiling of natural products with in vitro antiplasmodial activities and currently registered anti-malarial drugs
por: Egieyeh, Samuel Ayodele, et al.
Publicado: (2016) -
Computational drug repurposing strategy predicted peptide-based drugs that can potentially inhibit the interaction of SARS-CoV-2 spike protein with its target (humanACE2)
por: Egieyeh, Samuel, et al.
Publicado: (2021) -
Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds
por: Oselusi, Samson Olaitan, et al.
Publicado: (2021) -
Cheminformatic Profiling and Hit Prioritization of Natural Products with Activities against Methicillin-Resistant Staphylococcus aureus (MRSA)
por: Oselusi, Samson O., et al.
Publicado: (2021)