Nicolas Philippe

DiagAI, a machine-learning system, improves variant interpretation in genetic testing by prioritizing causal variants, outperforming existing tools with higher diagnostic yield and shorter variant shortlists.

This paper develops a symptom interaction model to address heterogeneous phenotype reporting in genetic disease, improving gene prioritization by 42%.

Genome Alert! automatically detects changes in variant classifications and gene-disease associations over time, improving clinical interpretation of genomic data with minimal human effort.

This paper introduces DE-kupl, a k-mer-based method to capture RNA variation without a reference, identifying novel transcripts and biological events from RNA-seq data.