Gelareh Mohammed Zadeh

KenazLBM is a model that characterizes and predicts brain states from raw iEEG data, generalizing across subjects with heterogeneous recording channels.

The paper introduces a method to assign single-cell RNA-seq data to donor-of-origin without prior genetic information, achieving high concordance in tumor-derived data.

This study combines bulk RNA-Seq datasets to create a transcriptomic landscape of meningiomas, identifies subtypes with distinct biology and prognosis, and provides an interactive tool for outcome prediction.