Predicting the Protein Corona on Nanoparticles Using Random Forest Models with Nanoparticle, Protein, and Experimental Features

We describe the predicted composition and abundance of the protein corona as a function of protein, nanoparticle, and experimental features that serve as the input dataset in which our Random Forest Regression (RFR) and Random Forest Classifier (RFC) models were trained on. Predictions were made using a supervised learning model, which was evaluated on an unseen test split of the data.