Alexandre H. Thiéry

This study benchmarks Nanopore long read RNA sequencing in human cell lines, showing improved isoform resolution compared to short reads.

This paper introduces m6Anet, a Multiple Instance Learning framework for detecting m6A methylation from direct RNA sequencing data, achieving performance comparable to experimental methods without retraining.

This paper introduces xPore, a method to detect differential RNA modifications from direct RNA sequencing, showing it identifies m6A sites with single base resolution and quantifies modification rate differences across cell lines.

NanoVar accurately detects structural variants using low-depth Nanopore sequencing, achieving high F1 score in simulated data and uncovering normal alleles in patient samples.