Stefano Maria Pagnotta

This paper links Gene Set Enrichment Analysis to the Lorenz curve from economics, showing their statistical relationship and conceptual parallels.

The paper applies an asymmetric transformation and supervised feature selection to single-cell RNA-Seq data to improve clustering and identify cluster-specific genes.

The paper introduces a web tool for Gene-Set Enrichment Analysis using the Mann-Witney test, improving computational efficiency and providing prioritization methods for enrichment results.

The paper introduces AWST, a data transformation method that improves clustering accuracy in RNA-seq data by reducing the need for gene selection.

The paper introduces scTHI, a method to identify ligand-receptor interactions in glioma using single-cell RNA sequencing data from six human datasets.