Raffaele Calogero

Ex vivo stem-like cell families model evolution of glioblastoma therapeutic resistance

This study develops a model using stem-like cells to study how glioblastoma evolves resistance to therapy.

UnifiedGreatMod: A New Holistic Modeling Paradigm for Studying Biological Systems on a Complete and Harmonious Scale

The paper introduces a new modeling paradigm, UnifiedGreatMod, that integrates fine-grained and coarse-grained biological information to study system behavior, demonstrating its application in simulating E. coli metabolism and analyzing cell responses to infection.

CONNECTOR, fitting and clustering of longitudinal data to reveal a new risk stratification system.

CONNECTOR analyzes longitudinal tumor growth data to identify clusters and reveal new molecular associations with therapy response.

Stardust: improving spatial transcriptomics data analysis through space aware modularity optimization based clustering.

Stardust improves spatial transcriptomics clustering by integrating spatial and transcriptomic data through modularity optimization, achieving more stable and biologically coherent results.

Different RNA profiles in plasma derived small and large extracellular vesicles of Neurodegenerative diseases patients.

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.

Sparsely-Connected Autoencoder (SCA) for single cell RNAseq data mining

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: reproducible Classification Analysis of Single Cell sequencing data

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.

Reproducible Bioinformatics Project: A community for reproducible bioinformatics analysis pipelines

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

Complementary information on single nucleotide variants, INDELs and functional translocations can be obtained with RNAseq using different library preparations

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.