Pierre Laurent‐Puig

fastCNV: Fast and accurate copy number variation prediction from High-Definition Spatial Transcriptomics and scRNA-Seq Data

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

A deep learning-based multiscale integration of spatial omics with tumor morphology.

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.

Multiethnic genome-wide association study of differentiated thyroid cancer in the EPITHYR consortium

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.