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Comparez modèles biologiques, moteurs de docking et flux de calcul côte à côte. Filtrez par modèle d'accès, empreinte de calcul et catégorie pour parvenir à une table de décision exploitable en moins d'une minute.
| Attribut | ＋ Ajouter un outil | |||
|---|---|---|---|---|
| Category | AI Drug Discovery | AI Drug Discovery | AI Drug Discovery | — |
| Subcategory | Molecular Property Prediction | Research AI Methods | Molecular Property Prediction | — |
| Company | Chemprop contributors | Research / method authors | Luo Lab | — |
| Access mode | Public code | Confirm distribution and exact release | Research code or publication | — |
| Licence conditions | Check repository and dataset licences | NOT_INDEPENDENTLY_AUDITED | Check code and model weights separately | — |
| Compute requirements | Version and workload dependent; not independently benchmarked | Version and data dependent | Check selected checkpoint and runtime; no GPU catalog recommendation | — |
| Biological application | Non enregistré | Non enregistré | Non enregistré | — |
| Research workflow | Non enregistré | Non enregistré | Non enregistré | — |
| Evidence level | Project documentation; no local benchmark | PEER_REVIEWED_METHOD_OR_CONFERENCE | Peer-reviewed primary method | — |
| Commercial eligibility | Confirm exact code, weights and data terms | NOT_INDEPENDENTLY_AUDITED | Unknown, requires audit | — |
| Price | See access and licence terms | Verify access and licence | Check selected model licence | — |
| Availability ⓘ | Public code | Method paper or official documentation | Public research method/code | — |
| Features | Message-passing molecular property prediction, Documented research workflow | ADMET-AI scientific method, Molecular SMILES with well-defined compound stereochemistry and relevant assay domain, Predicted absorption, distribution, metabolism, excretion and toxicity endpoints | Chemical foundation model for learned molecular representations, property prediction and conditional molecule generation., Molecular features, predicted properties or generated SMILES | — |
| Entry type | Research software / model | Source-scoped research method | Research AI model / method | — |
| AI role | Machine-learning software | ENSEMBLE_ML | Published biomedical AI method | — |
| Input data | Molecular structures and property labels | Molecular SMILES with well-defined compound stereochemistry and relevant assay domain | Valid SMILES; trained downstream endpoint or conditioned molecule task | — |
| Output data | Property predictions | Predicted absorption, distribution, metabolism, excretion and toxicity endpoints | Molecular features; predicted properties or generated SMILES | — |
| Validation | Evaluate on representative held-out data | Published method scope; no independent BioAtlas execution or benchmark | Requires independent dataset-specific evaluation | — |
| Type | Non enregistré | Non enregistré | Non enregistré | — |
| Intended use | Non enregistré | Non enregistré | Non enregistré | — |
| Compatibility | Non enregistré | Non enregistré | Non enregistré | — |