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Vergleichen Sie biologische Modelle, Docking-Engines und Berechnungs-Workflows Seite an Seite. Filtern Sie nach Zugangsmodell, Rechenbedarf und Kategorie, um in unter einer Minute zu einer verwertbaren Entscheidungstabelle zu gelangen.
| Attribut | ＋ Werkzeug hinzufügen | |||
|---|---|---|---|---|
| Category | Biological AI Models | Biological AI Models | Biological AI Models | — |
| Subcategory | Protein Design | Protein Design | Protein Design | — |
| Company | ProteinMPNN authors | Pacesa Lab | Boltz Team | — |
| Access mode | Public code | Research code or publication | Research code or publication | — |
| Licence conditions | Check code, dependencies and model terms | Check code and model weights separately | Check code and model weights separately | — |
| Compute requirements | Version and workload dependent; not independently benchmarked | Check selected checkpoint and runtime; no GPU catalog recommendation | Check selected checkpoint and runtime; no GPU catalog recommendation | — |
| Biological application | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Research workflow | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Evidence level | Project documentation; no local benchmark | Peer-reviewed primary method | Primary research preprint | — |
| Commercial eligibility | Confirm exact code, weights and data terms | Unknown, requires audit | Unknown, requires audit | — |
| Price | See access and licence terms | Check selected model licence | Check selected model licence | — |
| Availability ⓘ | Public code | Public research method/code | Public research method/code | — |
| Features | Protein sequence design from structure, Documented research workflow | AF2-guided optimization pipeline proposes protein binder designs for target structures., Candidate binder sequences, modeled protein complexes | Target-conditioned protein and peptide binder generation model as reported in its preprint., Binder sequence and structure candidates | — |
| Entry type | Research software / model | Research AI model / method | Research AI model / method | — |
| AI role | Machine-learning software | Published biomedical AI method | Published biomedical AI method | — |
| Input data | Protein backbone structures | Target protein 3D coordinates; AF2/MPNN workflow and target interface constraints | Target context; design constraints | — |
| Output data | Candidate amino-acid sequences | Candidate binder sequences; modeled protein complexes | Binder sequence and structure candidates | — |
| Validation | Evaluate on representative held-out data | Requires independent dataset-specific evaluation | Requires independent dataset-specific evaluation | — |
| Type | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Intended use | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Compatibility | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |