Cécile Badoual

APEX infers cancer gene expression from plasma cfChIP-seq data, outperforming existing methods and enabling subtype classification and biomarker identification.

The paper introduces a spatial multi-omics approach combining protein and transcriptome analysis to characterize human cancer tissue from a single section, revealing immune phenotypes and cellular states.

This study develops a deep learning model to classify head and neck squamous lesions with confidence scores to identify uncertain predictions.

This study compares two HPV detection assays on FFPE head and neck cancer biopsies, finding good agreement with some discrepancies due to low viral load.