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Confronta modelli biologici, motori di docking e flussi di calcolo affiancati. Filtra per modello di accesso, impronta di calcolo e categoria per ottenere una tabella decisionale attuabile in meno di un minuto.
| Attributo | ＋ Aggiungi strumento | |||
|---|---|---|---|---|
| Category | Single-cell, Spatial & Cytometry | Single-cell, Spatial & Cytometry | Single-cell, Spatial & Cytometry | — |
| Subcategory | Perturbation Models | Conventional or Statistical Baselines | Conventional or Statistical Baselines | — |
| Company | scverse / Pertpy contributors | Research / method authors | Research / method authors | — |
| Access mode | Public code / project terms | Confirm distribution and exact release | Confirm distribution and exact release | — |
| Licence conditions | Review code, weights, data and service terms separately | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | — |
| Compute requirements | See source requirements for selected configuration | Version and data dependent | Version and data dependent | — |
| Biological application | Non registrato | Non registrato | Non registrato | — |
| Research workflow | Non registrato | Non registrato | Non registrato | — |
| Evidence level | Project/provider documentation; no local benchmark | OFFICIAL_DOCUMENTATION | PEER_REVIEWED_METHOD_OR_CONFERENCE | — |
| Commercial eligibility | Not independently confirmed | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | — |
| Price | See project terms; compute costs may apply | Verify access and licence | Verify access and licence | — |
| Availability ⓘ | See project release and maintenance status | Method paper or official documentation | Method paper or official documentation | — |
| Features | Framework for single-cell perturbation analysis, Input: Perturbation datasets and experimental metadata, Output: Perturbation distances and cell-response analyses | Azimuth (Seurat reference mapping) scientific method, Compatible single-cell expression matrix and named atlas reference, Anchor-based reference map and predicted cell labels | Baysor scientific method, Subcellular in-situ transcript positions and optional cell stain masks, Spatial transcript-informed cell boundaries | — |
| Entry type | Research software / framework | Classical/statistical scientific method | Classical/statistical scientific method | — |
| AI role | Method-dependent scientific ML workflow | NON_AI_REFERENCE | NON_AI_STATISTICAL | — |
| Input data | Perturbation datasets and experimental metadata | Compatible single-cell expression matrix and named atlas reference | Subcellular in-situ transcript positions and optional cell stain masks | — |
| Output data | Perturbation distances and cell-response analyses | Anchor-based reference map and predicted cell labels | Spatial transcript-informed cell boundaries | — |
| Validation | Non registrato | Published method scope; no independent BioAtlas execution or benchmark | Published method scope; no independent BioAtlas execution or benchmark | — |
| Type | Non registrato | Non registrato | Non registrato | — |
| Intended use | Biological and pharmaceutical research | Non registrato | Non registrato | — |
| Compatibility | Non registrato | Non registrato | Non registrato | — |
| Limitations | Methods have different statistical assumptions; the framework is not a single predictive virtual-cell model. | Non registrato | Non registrato | — |