Pierre Laurent‐Puig

fastCNV predicts copy number variations from spatial transcriptomics and scRNA-seq data, showing high accuracy and speed improvements over existing methods.

This paper introduces MISO, a deep learning method that predicts spatial transcriptomics data from H&E slides, enabling spatially resolved gene expression and patient representation for downstream tasks.

The paper identifies two TRM subpopulations in NSCLC patients and shows that only DP TRM predicts response to PD-1 blockade immunotherapy.

This study identifies genetic risk loci for differentiated thyroid cancer in multiethnic populations, finding novel associations and allele frequency differences between Oceanian and European ancestry groups.