Laurent Guyon

This study uses 3D invasion models of RCC cell lines to predict their metastatic potential in vivo, showing that 3D models better reflect in vivo behavior than 2D assays.

This study benchmarks miRNA target prediction algorithms using single-cell co-sequencing data, showing varying performance across species and target numbers.

The paper characterizes avirulent P. aeruginosa strains lacking T3SS genes, showing they produce variable secondary metabolites despite low cytotoxicity.

This paper benchmarks the impact of sequencing depth and patient number on survival prediction using miRNA-seq and mRNA-seq with Cox and random survival forest models.

The paper benchmarks lasso-like penalties in Cox models for TCGA datasets, showing improved performance with pre-filtering and highlighting cancer-specific differences.

miRViz is a webserver for visualizing and interpreting miRNA datasets to identify significant differentially expressed miRNAs.