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| Attribut | ＋ Werkzeug hinzufügen | |||
|---|---|---|---|---|
| Category | Genomics & Sequence Modeling | Genomics & Bioinformatics | Genomics & Bioinformatics | — |
| Subcategory | Long-Range Genomic Foundation Models | Regulatory Genomics | Conventional or Statistical Baselines | — |
| Company | Stanford University (Hazy Research) | Google DeepMind | Research / method authors | — |
| Access mode | Open Source | Research code or publication | Confirm distribution and exact release | — |
| Licence conditions | Apache 2.0 | Check code and model weights separately | NOT_INDEPENDENTLY_AUDITED | — |
| Compute requirements | 1x GPU (A100 or H100 recommended for 1M context) | Check selected checkpoint and runtime; no GPU catalog recommendation | Version and data dependent | — |
| Biological application | Enhancer-promoter interaction prediction, chromatin profile modeling, and splicing regulation | Nicht erfasst | Nicht erfasst | — |
| Research workflow | Input long DNA sequence -> predict regulatory activity, chromatin marks, and variant effects | Nicht erfasst | Nicht erfasst | — |
| Evidence level | Peer-reviewed research (NeurIPS 2023) | Peer-reviewed primary method | PEER_REVIEWED_METHOD_OR_CONFERENCE | — |
| Commercial eligibility | Open source release | Unknown, requires audit | NOT_INDEPENDENTLY_AUDITED | — |
| Price | Free Open Source | Check selected model licence | Verify access and licence | — |
| Availability ⓘ | Available on GitHub and Hugging Face | Public research method/code | Method paper or official documentation | — |
| Features | Sub-quadratic scaling allowing context lengths up to 1,000,000 base pairs, Single-nucleotide resolution without k-mer tokenization artifacts, Trained on the human reference genome (T2T-CHM13), State-of-the-art benchmarks across the Genomic Benchmarks suite | Predicts genomic regulatory tracks and predicted functional effects of noncoding DNA variants., Genomic regulatory track, sequence-variant contrast | bcftools scientific method, Reference genome with aligned short-read input and correct ploidy assumptions, VCF/BCF variant calls and variants QC operations | — |
| Entry type | AI Model | Research AI model / method | Classical/statistical scientific method | — |
| AI role | Long-Range Sequence Modeling | Published biomedical AI method | NON_AI_STATISTICAL | — |
| Input data | Nicht erfasst | DNA sequence interval; alleles and tissue/assay ontology | Reference genome with aligned short-read input and correct ploidy assumptions | — |
| Output data | Nicht erfasst | Genomic regulatory track; sequence-variant contrast | VCF/BCF variant calls and variants QC operations | — |
| Validation | Nicht erfasst | Requires independent dataset-specific evaluation | Published method scope; no independent BioAtlas execution or benchmark | — |
| Type | Long-context genomic foundation model | Nicht erfasst | Nicht erfasst | — |
| Intended use | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Compatibility | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Manufacturer | Stanford University | Nicht erfasst | Nicht erfasst | — |
| Integration evidence | https://github.com/HazyResearch/hyena-dna | Nicht erfasst | Nicht erfasst | — |
| Laboratory handoff | Identifies candidate non-coding regulatory elements for CRISPR perturbation validation | Nicht erfasst | Nicht erfasst | — |