Fabrice André

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

Novae is a graph-based foundation model for spatial transcriptomics that improves domain inference and batch correction across multiple tissues and technologies.

This study uses scRNA-seq to compare treatment-naive and post-treatment colorectal cancer samples, identifying markers and cell types associated with chemoresistance and response.

This paper develops a method using circulating DNA fragment end motifs and machine learning to detect cancer with high accuracy across multiple cancer types.

Sopa provides a technology-invariant pipeline for analyzing image-based spatial-omics data, offering unified visualization and analysis tools.

The paper shows that intronic polyadenylation (IPA) of MET affects tumour progression and therapy resistance by producing a short MET isoform that reduces invasiveness and enhances response to MAPK-targeted therapy.