The development of a biomolecular cancer model starts with the acquisition of nodes from diverse multiscale sources. We integrate omics datasets from Genomic Data Commons (GDC), frequently mutated nodes, cancer signature genes, and therapeutic targets to ensure biological relevance and translational potential.

The enriched node set is integrated into a comprehensive interactome using public databases such as INDRA, TRRUST, SIGNOR, and Omnipath. These resources inform activations and inhibitions, enabling the construction of a biologically informed network that maps essential molecular interactions and regulatory mechanisms.

The resulting models capture the regulatory logic of tumor-specific networks and serve as scaffolds for downstream data annotation and analysis. These models can be integrated with external tools to explore patient-specific behaviors, therapeutic responses, and personalized treatment strategies—advancing translational applications in precision oncology.