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README.md

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-license: cc-by-4.0
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+# Structural Disease Networks — TCGE Benchmark
+
+A curated collection of disease signaling networks analyzed with 
+the Theory of Emergent Global Constraints (TCGE) framework.
+
+## Overview
+- **Networks**: 100+ disease signaling networks
+- **Domains**: Oncology, Pneumology, Neurology, Immunology
+- **Metrics**: Fragility Index (FI), algebraic connectivity (λ₂), 
+  spectral entropy (EPS_z), edge criticality, bridge analysis
+- **Drugs mapped**: 50+ approved therapies with structural profiles
+
+## Key Finding
+The Fragility Index predicts therapeutic response class:
+- FI > 90%: Ultra-fragile → treatment-refractory (COPD)
+- FI ≥ 80%: Hyper-fragile → structural restoration transforms outcome (CF/Trikafta)
+- FI > 60%: Fragile → monotherapy works (asthma, IPF)
+- FI ≈ 50%: Resilient → combination required (NSCLC)
+
+## Platform
+Full analysis engine: https://cognitive-engineering.dev
+
+## Citation
+
+If you use this dataset, please cite:
+
+@article{venti2026structural,
+  title={Protein regulatory architectures segregate into two topological 
+         regimes: distributed cooperative systems and fragile signalling cascades},
+  author={Venti, David Martin},
+  year={2026},
+  doi={10.5281/zenodo.19045028}
+}
+
+@article{venti2026triangular,
+  title={Triangular solidification: local motif redundancy drives a sharp 
+         structural transition in complex networks},
+  author={Venti, David Martin},
+  year={2026},
+  doi={10.5281/zenodo.19163066}
+}
+
+## License
+CC BY 4.0