Mélina Gallopin

phyloDS identifies differentially used orthologous splice junctions across species by improving orthology definition, statistical testing, and sequence-level validation.

This paper introduces phyloDE, a method for interspecies differential gene expression analysis that controls FDR and identifies more DE genes with consistent cis-regulatory changes.

Metappuccino uses a fine-tuned large language model to enrich metadata from RNA-seq datasets, improving accuracy and consistency for cancer research.

The paper compares machine learning models to predict mutation status in AML patients using RNA-seq data, finding complex models achieve high accuracy for NPM1, IDH1/IDH2, and FLT3-ITD mutations.

KaMRaT reduces the dimensionality of k-mer count matrices from high-throughput sequencing data to identify condition-specific sequences.

The paper develops a workflow to generate 3D chromosome models from Hi-C data and applies it to fungal species, revealing new structural insights.

This paper benchmarks differential gene expression analysis methods for inter-species RNA-Seq data using a phylogenetic simulation framework to evaluate their performance across species.

The paper uses a k-mer based method to analyze RNA-seq data at the nucleotide level in lung adenocarcinoma, identifying novel tumor-specific RNA features and their clinical relevance.

The paper introduces a reference-free computational method to identify novel RNAs for prostate cancer diagnosis, finding that 9 unannotated lncRNAs outperform existing biomarkers.

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.