EvoDiff
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Microsoft's EvoDiff combines evolutionary-scale protein data with diffusion models for controllable protein generation in sequence space.
Sequence-space diffusion: Operates directly in protein-sequence space rather than structure space, enabling generation of proteins that structure-based models can't reach.
Evolutionary-scale training: Trains on massive evolutionary protein datasets, leveraging the diverse biological sequence space as learning signal.
Controllable generation: Supports conditional generation on function, family, or motif constraints, giving researchers practical design levers.
Beyond structure-based models: Generates proteins that are inaccessible to structure-based generators (e.g., those without well-defined folds), expanding the design space.
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