Rocco Piazza

This study shows that Pcdh9 deletion in mice causes synaptic overgrowth and excitatory transmission defects in the hippocampus, revealing its role in synaptic morphology and function.

The paper identifies hemogenic endothelium in vitelline and umbilical arteries as a major source of fetal lympho-myeloid progenitors in mice, showing their transient contribution before definitive HSCs emerge.

This study identifies cancer type-specific evolutionary signatures using genomic data from over 35,000 patients, revealing patterns of driver mutation acquisition linked to prognosis.

The paper shows that SET levels influence enhancer usage during cell fate acquisition, leading to altered gene regulation and contributing to disease.

This study identifies low-frequency mutations in SARS-CoV-2 deep sequencing data to detect variants earlier than consensus-based methods, using 220,788 samples.

The paper uses variant calling from scRNA-seq data to identify potential sample swaps between patient-derived cell lines.

The paper analyzes SARS-CoV-2 synonymous mutations across 400,000 samples, showing that mutations increasing codon similarity to human codons tend to persist, suggesting adaptation to human host codon usage.

This paper introduces LACE, a framework for analyzing longitudinal single-cell mutation data to model cancer evolution and therapy response.

The paper analyzes SARS-CoV-2 genomic diversity to reveal mutational signatures and host responses, showing heterogeneous genomic architectures and the role of purifying selection and transmission dynamics.

VERSO improves viral phylogenetic inference and quantifies intra-host diversity using clonal variant profiles and variant frequency patterns, outperforming existing tools on simulations and real data.

This paper applies optimal control theory to design personalized cancer therapies, showing that individual pharmacokinetic differences significantly impact treatment outcomes.

OncoScore is a text-mining tool that ranks genes by their association with cancer, achieving high accuracy in prioritizing cancer-related genes.