Combine features inside the model
An elastic-network model such as GNM relates a contact network to collective behavior. The coupled BioTwin profile modifies that operator using selected geometric, topological, confidence and hydropathy information. This differs from simply listing several descriptor scores: their coupling can change the modes produced by the model.
Two related research profiles
A separate demonstrator evolves a small density-matrix representation under specified coupling and jump terms. QuTiP and other established tools already supply master-equation machinery; the scientific question is whether the chosen biological encoding predicts something useful. Density-matrix notation alone supplies no evidence of a quantum biological mechanism.
A nominated vulnerability must survive simpler explanations
Historical computational work distinguished some coarse classes while performing poorly on finer mechanism distinctions. Each added descriptor therefore needs an ablation against the simpler model. A useful candidate could proceed to inverse allostery and physical-reach analysis to ask how it might be acted on. That composition is a hypothesis to test, not an established gain from adding more inputs.