Marc Santolini

The paper identifies peripheral and core genes in the human interactome using gene expression data and shows their distinct biological roles and implications for disease classification and drug targets.

The paper integrates existing interactome data with new experimental interactions to identify a COPD-related disease network module.

The paper predicts biochemical perturbation patterns using network topology, achieving 65-80% accuracy without kinetic parameters.

The paper identifies NFATC4 as a key regulator of Type 2 Diabetes genes by analyzing a gene regulatory network in pancreatic islets and linking it to eQTLs and differential expression.

The paper quantifies variability in cardiac ion conductances across a genetically diverse mouse population and shows compensatory mechanisms between Ca2+ and K+ currents.

The paper identifies disease-associated genes missed by traditional methods using a personalized differential gene expression analysis in a genetically diverse mouse model of cardiac hypertrophy and heart failure.