In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

This open-access Nature Communications paper describes in silico Pathway Activation Network Decomposition Analysis (iPANDA)—a workflow that layers gene coexpression modules, pathway topology, and differential expression weights to compute pathway activation scores. The authors show that iPANDA dramatically reduces cross-platform noise in MAQC benchmark data and, crucially, delivers pathway signatures that stratify paclitaxel-treated breast cancer patients by therapeutic response, highlighting circuits such as ERBB, PTEN, BRCA1, and TGF-β as reproducible biomarkers across independent cohorts. citeturn0search1