Marco Pagni

StereoMapper clarifies metabolite identity by assigning stereochemically aware relationships, achieving high performance in benchmark datasets and improving GEM accuracy.

This study uses Dictyostelium discoideum to investigate host responses to Mycobacterium marinum infection, identifying Atg9's role in maintaining vacuole integrity and restricting bacterial growth.

The paper identifies oxalotrophy as a rare metabolic trait in the human microbiome, primarily confined to the gut, and finds evidence of horizontal gene transfer for the trait.

This study analyzes microbiome data from multiple OA cohorts and finds no significant differences between OA patients and controls, attributing microbiome changes to age and BMI instead of OA.

The paper demonstrates biocontrol using oxalotrophic bacteria to combat Aspergillus niger in a mouse infection model by interfering with oxalic acid production.

Standard-GEM provides a template for reproducible genome-scale metabolic model development following FAIR principles and software best practices.

MetaNetX/MNXref provides a unified namespace for metabolites and reactions, improving reconciliation between biochemistry databases and GSMNs with enhanced mapping tools.

This study uses time-resolved RNA-seq to analyze D. discoideum gene expression during M. marinum infection, identifying key pathways involved in host response to damage, stress, and metabolic adaptation.

The paper introduces metaboGSE, a method for gene set enrichment analysis using condition-specific metabolic sub-networks, showing higher specificity than GSEA and topGO.