Maddalena Arigoni

This paper introduces GERALT, a genetic circuit that enables TGFβ-independent hiPSC renewal and inducible lineage programming, improving differentiation efficiency and reducing medium complexity.

REBEL resolves dependency issues in bioinformatics by providing a reproducible environment framework that improves installation success rates and enables deterministic builds.

The paper compares RNA profiles in plasma-derived large and small extracellular vesicles from neurodegenerative disease patients and healthy controls, identifying disease-specific miRNA signatures.

The paper evaluates the sparsely-connected autoencoder (SCA) for functional mining of single-cell RNA-seq clusters, showing its ability to uncover hidden features and improve cluster reconstruction.

rCASC provides a reproducible RNA-seq analysis workflow for single-cell data, enabling functional and computational reproducibility from counts generation to cell sub-population signature identification.

The paper introduces a reproducible bioinformatics project framework using Docker and R to ensure consistent and replicable analysis workflows across different systems.

The paper compares two RNA-seq library preparation protocols, showing ACCESS detects more coding SNVs/INDELs but POLYA is better for UTRs, with no advantage for fusion transcripts.