A hybrid chemoinformatics approach integrating caputo fractional-derivative graph invariants and artificial neural network for modeling of anti-sickle cell compounds
Abstract Cheminformatics focuses on the accurate prediction of physicochemical properties, which plays a crucial role in molecular modeling and materials science, as experimental determination is often time-consuming and costly. In this study, we propose a machine learning based framework for predicting physicochemical...
Naveed Iqbal, Wakeel Ahmed, Muhammad Waseem Akram et al.
· Scientific Reports · 0 citations