Multi-omics data integration and machine learning for complex disease subtyping

Developed computational workflows for the integration of multi-view omics data to improve patient stratification. The project applies also clustering and classification techniques to clinical and molecular datasets to identify biological patterns and characterize subtypes in complex diseases.

Project 1: clustering of heart failure data

• Assignment given by the Professor
• Heart Failure Dataset
• Solution in a Python Notebook

Project 2: integration of omics views of PDAC data

• PDAC Dataset
• MOFA weights
• Solution in a Python Notebook

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Repository for the projects assigned during the Scientific Visualization course, UNIMI, AY 2025/2026, by Hari Calzi & Salvatore Ferrara.