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| Atributo | ＋ Añadir herramienta | |||
|---|---|---|---|---|
| Category | Genomics & Sequence Modeling | Genomics & Bioinformatics | Genomics & Bioinformatics | — |
| Subcategory | 3D Variant Pathogenicity | Regulatory Genomics | Conventional or Statistical Baselines | — |
| Company | Illumina Artificial Intelligence Lab | Google DeepMind | Research / method authors | — |
| Access mode | Open Access for Research | Research code or publication | Confirm distribution and exact release | — |
| Licence conditions | Academic non-commercial use | Check code and model weights separately | NOT_INDEPENDENTLY_AUDITED | — |
| Compute requirements | Pre-computed genome-wide lookup table / GPU inference | Check selected checkpoint and runtime; no GPU catalog recommendation | Version and data dependent | — |
| Biological application | Rare disease genetic diagnosis, carrier screening, and drug target discovery | No registrado | No registrado | — |
| Research workflow | Patient genomic variant -> query 3D pathogenicity score | No registrado | No registrado | — |
| Evidence level | Peer-reviewed research (Science 2023) | Peer-reviewed primary method | PEER_REVIEWED_METHOD_OR_CONFERENCE | — |
| Commercial eligibility | Open access for non-commercial research; Illumina platform integration | Unknown, requires audit | NOT_INDEPENDENTLY_AUDITED | — |
| Price | Free for academic research | Check selected model licence | Verify access and licence | — |
| Availability ⓘ | Available via Illumina GitHub and Connected Analytics | Public research method/code | Method paper or official documentation | — |
| Features | Trained on benign variants identified across 233 diverse primate species, Directly incorporates 3D structural protein atomic coordinate representations, Outperforms previous variant classification tools on ClinVar and UK Biobank cohorts, Classifies variants of unknown significance (VUS) in rare genetic disorders | 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 & Database | Research AI model / method | Classical/statistical scientific method | — |
| AI role | 3D Structural Variant Classification | Published biomedical AI method | NON_AI_STATISTICAL | — |
| Input data | No registrado | DNA sequence interval; alleles and tissue/assay ontology | Reference genome with aligned short-read input and correct ploidy assumptions | — |
| Output data | No registrado | Genomic regulatory track; sequence-variant contrast | VCF/BCF variant calls and variants QC operations | — |
| Validation | No registrado | Requires independent dataset-specific evaluation | Published method scope; no independent BioAtlas execution or benchmark | — |
| Type | 3D deep learning variant pathogenicity classifier | No registrado | No registrado | — |
| Intended use | No registrado | No registrado | No registrado | — |
| Compatibility | No registrado | No registrado | No registrado | — |
| Manufacturer | Illumina, Inc. | No registrado | No registrado | — |
| Integration evidence | https://github.com/illumina/PrimateAI-3D | No registrado | No registrado | — |
| Laboratory handoff | Directly used in clinical genetics diagnostic reporting | No registrado | No registrado | — |