Loading BioAtlas...
Loading BioAtlas...
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 | Genomics & Sequence Modeling CaduceusStanford University & Princeton UniversityCodice aperto🖥️ GPU RTX | ＋ Aggiungi strumento |
|---|---|---|
| Category | Genomics & Sequence Modeling | — |
| Subcategory | Bi-directional Mamba Genomic Models | — |
| Company | Stanford University & Princeton University | — |
| Access mode | Open Source | — |
| Licence conditions | Apache 2.0 | — |
| Compute requirements | 1x GPU (>= 16GB VRAM) | — |
| Biological application | Long-range gene regulation, promoter-enhancer mapping, and variant impact scoring | — |
| Research workflow | Genomic DNA sequence -> predict regulatory activity with RC equivariance | — |
| Evidence level | Peer-reviewed research (ICML 2024) | — |
| Commercial eligibility | Open source release | — |
| Price | Free Open Source | — |
| Availability ⓘ | Available on GitHub and Hugging Face | — |
| Features | Bi-directional state space (Mamba) architecture overcoming causal autoregressive limitations, Guaranteed reverse-complement (RC) equivariance essential for double-stranded DNA modeling, Sub-quadratic scaling allowing 131k base pair context on single standard GPUs, Superior performance on variant effect and chromatin accessibility benchmarks | — |
| Entry type | AI Model | — |
| AI role | Equivariant State Space Modeling | — |
| Input data | Non registrato | — |
| Output data | Non registrato | — |
| Validation | Non registrato | — |
| Type | Bi-directional Mamba genomic model | — |
| Intended use | Non registrato | — |
| Compatibility | Non registrato | — |
| Manufacturer | Stanford University & Princeton University | — |
| Integration evidence | https://github.com/kuleshov-group/caduceus | — |
| Laboratory handoff | Informs non-coding variant prioritization for CRISPR functional genomics | — |