Targeted proteomic analysis of aqueous humor in idiopathic uveitis and Vogt-Koyanagi-Harada syndrome

ABSTRACT: Extreme gradient boosting (XGBoost), an efficient and robust machine learning algorithm, was used to develop a model for classifying the IU, VKH, and control groups. The three proteins deemed most important were transferrin (TF), calsyntenin-1 (CLSTN1), and retinol-binding protein 4 (RBP4), which represent a promising biomarker panel. These proteins were validated by high-resolution multiple reaction monitoring (HR-MRM) in a validation cohort.

ORGANISM(S): Homo Sapiens

SUBMITTER: Xiaomin Zhang  

PROVIDER: PXD043575 | iProX | Thu Jul 06 00:00:00 GMT+01:00 2023

REPOSITORIES: iProX