Code and data for: Hybrid Computational Modeling with Multi-Level Validation Identifies TK1-VIM as a Robust Therapeutic Pair in Triple-Negative Breast Cancer
Assunção Monteiro, Sérgio; Vidal de Carvalho, Luis Alfredo; Waghabi, Mariana; Silva, Fabricio;
Code and data for: Hybrid Computational Modeling with Multi-Level Validation Identifies TK1-VIM as a Robust Therapeutic Pair in Triple-Negative Breast Cancer
This repository contains all code, raw data, and supplementary tables to reproduce the computational analyses of manuscript ijms-4337060 (International Journal of Molecular Sciences, MDPI). The pipeline combines Boolean network simulation, semidefinite programming (SDP) optimisation via CVXPY/SCS, and AlphaGenome regulatory variant effect prediction to identify TK1-VIM as a computationally nominated therapeutic candidate pair in triple-negative breast cancer (TNBC). Includes: 5 Python scripts, AlphaGenome v3 raw outputs (JSON), 5 supplementary tables (xlsx), and audit evidence of ontology correction made during peer review.