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

ABSTRACT: 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.

INSTRUMENT(S):

ORGANISM(S): Bos Taurus (bovine)

TISSUE(S): Blood Serum

SUBMITTER: Nicole Vijgen

LAB HEAD: Christine K.

PROVIDER: PXD053700 | Pride | 2025-08-04

REPOSITORIES: Pride

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			Action	DRS
	ID101054_01_OTIT_FSN20357_10020_012423.index	Other
	ID101054_01_OTIT_FSN20357_10020_012423.raw	Raw
	ID101055_01_OTIT_FSN20357_10020_012423.index	Other
	ID101055_01_OTIT_FSN20357_10020_012423.raw	Raw
	ID101056_01_OTIT_FSN20357_10020_012423.index	Other

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