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An Exploration of the Antiproliferative Potential of Chalcones and Dihydropyrazole Derivatives in Prostate Cancer via Androgen Receptor: Combined QSAR, Machine Learning, and Molecular Docking Techniques
Article (Web of Science)
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Research
Additional Document Info
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cited authors
Oyeneyin, O. E.; Obadawo, B. S.; Metibemu, D. S.; Owolabi, T. O.; Olanrewaju, A. A.; Orimoloye, S. M.; Ipinloju, N.; Olubosede, O.
publication date
January 1, 2022
webpage
Web of Science
published in
PHYSICAL CHEMISTRY RESEARCH
Journal
Research
category
CHEMISTRY, MULTIDISCIPLINARY
Category
keywords
Anticancer properties
Computer-aided drug design
Data science
Extreme learning machine
Additional Document Info
start page
211
end page
223
volume
10
issue
2