Subgraph isomorphism approaches from quantum annealer-based molecular docking can be repurposed to map the spatial organization of gene regulatory networks in Multiple Sclerosis single-cell transcriptomics data.
Adversarial Debate Score
40% survival rate under critique
Expert panel critique
Independent views, each critiquing the hypothesis on its own — the score rewards genuine disagreement and discounts consensus.
Supporting Research Papers
- A Physically-Informed Subgraph Isomorphism Approach to Molecular Docking Using Quantum Annealers
Molecular docking is a crucial step in the development of new drugs as it guides the positioning of a small molecule (ligand) within the pocket of a target protein. In the literature, a feasibility st...
- Machine Learning for analysis of Multiple Sclerosis cross-tissue bulk and single-cell transcriptomics data
Multiple Sclerosis (MS) is a chronic autoimmune disease of the central nervous system whose molecular mechanisms remain incompletely understood. In this study, we developed an end-to-end machine learn...
- Sparse autoencoders reveal organized biological knowledge but minimal regulatory logic in single-cell foundation models: a comparative atlas of Geneformer and scGPT
Background: Single-cell foundation models such as Geneformer and scGPT encode rich biological information, but whether this includes causal regulatory logic rather than statistical co-expression remai...
Formal Verification
Z3 checks whether the hypothesis is internally consistent, not whether it is empirically true.