{"count":5,"items":[{"article":null,"cancer_slugs":["pan-cancer"],"category":"protein-structure","confidence":"high","developer":"Google DeepMind","hf":null,"kind":"foundation","license":"Apache-2.0 (code) / CC-BY-4.0 (parameters)","links":{"demo":"https://alphafold.ebi.ac.uk/","docs":null,"doi":"10.1038/s41586-021-03819-2","github":"https://github.com/google-deepmind/alphafold","huggingface":null,"paper":"https://www.nature.com/articles/s41586-021-03819-2","pmid":null},"modalities":["protein-sequence"],"name":"AlphaFold 2","openness":"open-weights","regulatory_status":"not-applicable","release_date":"2021-07-15","settings":["basic-research","drug-discovery"],"slug":"alphafold","summary":"Przewiduje struktur\u0119 3D bia\u0142ka z sekwencji aminokwasowej z dok\u0142adno\u015bci\u0105 blisk\u0105 eksperymentalnej; baza AlphaFold Protein Structure Database (z EMBL-EBI) udost\u0119pnia przewidywane struktury ponad 200 milion\u00f3w bia\u0142ek, w tym cel\u00f3w istotnych w onkologii.","tasks":["protein-structure"],"url":"/ai-oncology/models/alphafold","verified_at":"2026-09-05T22:26:00.969670","version":"2"},{"article":null,"cancer_slugs":["pan-cancer"],"category":"protein-structure","confidence":"high","developer":"Google DeepMind / Isomorphic Labs","hf":null,"kind":"foundation","license":"CC-BY-NC-SA 4.0 (code); model parameters under academic non-commercial terms","links":{"demo":"https://alphafoldserver.com/","docs":null,"doi":"10.1038/s41586-024-07487-w","github":"https://github.com/google-deepmind/alphafold3","huggingface":null,"paper":"https://www.nature.com/articles/s41586-024-07487-w","pmid":null},"modalities":["protein-sequence","molecules","genomics"],"name":"AlphaFold 3","openness":"gated-weights","regulatory_status":"not-applicable","release_date":"2024-05-08","settings":["basic-research","drug-discovery"],"slug":"alphafold-3","summary":"Nast\u0119pca oparty na dyfuzji, przewiduj\u0105cy wsp\u00f3lne struktury bia\u0142ek z DNA, RNA, ligandami, jonami i zmodyfikowanymi resztami \u2014 typy oddzia\u0142ywa\u0144 kluczowe w projektowaniu lek\u00f3w i w rozumieniu kompleks\u00f3w onkogennych.","tasks":["protein-structure","drug-discovery"],"url":"/ai-oncology/models/alphafold-3","verified_at":"2026-09-05T22:26:00.993178","version":"3"},{"article":null,"cancer_slugs":["pan-cancer"],"category":"protein-structure","confidence":"high","developer":"Meta AI (FAIR)","hf":{"downloads":1303383,"fetched_at":"2026-09-09T21:33:09Z","gated":false,"last_modified":"2023-03-21","library":"transformers","license":"mit","likes":89,"pipeline_tag":"fill-mask"},"kind":"foundation","license":"MIT","links":{"demo":null,"docs":null,"doi":"10.1126/science.ade2574","github":"https://github.com/facebookresearch/esm","huggingface":"https://huggingface.co/facebook/esm2_t33_650M_UR50D","paper":"https://www.science.org/doi/10.1126/science.ade2574","pmid":null},"modalities":["protein-sequence"],"name":"ESM-2 / ESMFold","openness":"open-weights","regulatory_status":"not-applicable","release_date":"2022-11-01","settings":["basic-research","drug-discovery"],"slug":"esm-2","summary":"Modele j\u0119zykowe bia\u0142ek od 8 mln do 15 mld parametr\u00f3w trenowane na sekwencjach UniRef; wektory cech zasilaj\u0105 przewidywanie skutku wariant\u00f3w i funkcji, a ESMFold przewiduje struktur\u0119 wprost z jednej sekwencji bez MSA.","tasks":["feature-extraction","variant-effect","protein-structure"],"url":"/ai-oncology/models/esm-2","verified_at":"2026-09-05T22:26:01.022006","version":null},{"article":null,"cancer_slugs":["pan-cancer"],"category":"genomics","confidence":"high","developer":"Theodoris Lab (Gladstone Institutes / UCSF)","hf":{"downloads":1698,"fetched_at":"2026-09-09T21:33:08Z","gated":false,"last_modified":"2026-05-26","library":"transformers","license":"apache-2.0","likes":311,"pipeline_tag":"fill-mask"},"kind":"foundation","license":"apache-2.0","links":{"demo":null,"docs":null,"doi":"10.1038/s41586-023-06139-9","github":null,"huggingface":"https://huggingface.co/ctheodoris/Geneformer","paper":"https://www.nature.com/articles/s41586-023-06139-9","pmid":null},"modalities":["single-cell","transcriptomics"],"name":"Geneformer","openness":"open-weights","regulatory_status":"not-applicable","release_date":"2023-05-31","settings":["basic-research","drug-discovery"],"slug":"geneformer","summary":"Transformer pretrenowany na rankingach ekspresji w pojedynczych kom\u00f3rkach, kt\u00f3ry uczy si\u0119 kontekstu sieci genowych i pozwala przy niewielu danych przewidywa\u0107 skutki dawki genu, stany kom\u00f3rek i kandydackie cele terapeutyczne. Wersja z 2023 r. by\u0142a pretrenowana na Genecorpus-30M (ok. 30 mln ludzkich transkryptom\u00f3w pojedynczych kom\u00f3rek); od grudnia 2024 r. autorzy udost\u0119pniaj\u0105 wersj\u0119 V2 (warianty 104 mln i 316 mln parametr\u00f3w) pretrenowan\u0105 na Genecorpus-104M oraz wariant douczany na ok. 14 mln transkryptom\u00f3w nowotworowych.","tasks":["single-cell","gene-expression","feature-extraction","drug-discovery"],"url":"/ai-oncology/models/geneformer","verified_at":"2026-09-07T07:05:05.599962","version":null},{"article":null,"cancer_slugs":["pan-cancer"],"category":"drug-discovery","confidence":"medium","developer":"Zitnik Lab, Harvard Medical School","hf":null,"kind":"task-model","license":"MIT","links":{"demo":null,"docs":null,"doi":"10.1038/s41591-024-03233-x","github":"https://github.com/mims-harvard/TxGNN","huggingface":null,"paper":"https://www.nature.com/articles/s41591-024-03233-x","pmid":null},"modalities":["molecules","literature"],"name":"TxGNN","openness":"open-weights","regulatory_status":"research-only","release_date":"2024-09-25","settings":["drug-discovery"],"slug":"txgnn","summary":"Grafowa sie\u0107 neuronowa do repozycjonowania lek\u00f3w zero-shot, oceniaj\u0105ca wskazania i przeciwwskazania lek\u2013choroba na grafie wiedzy medycznej obejmuj\u0105cym 17 080 chor\u00f3b, w tym takie bez zatwierdzonego leczenia.","tasks":["drug-repurposing","drug-discovery"],"url":"/ai-oncology/models/txgnn","verified_at":"2026-09-05T22:26:01.078860","version":null}],"standard":"https://cancer3.ai/docs/ai-model-card","vocab":{"confidence":["high","medium","low"],"dataset_access":["open","registration","dua","controlled","commercial"],"dataset_kinds":["dataset","registry","benchmark","biobank","corpus"],"formats":["SVS","TIFF","NDPI","DICOM","NIfTI","PNG","JPEG","CSV","TSV","JSON","Parquet","FASTQ","BAM","VCF","MAF","h5ad","PDB","mmCIF","text","other"],"kinds":["foundation","task-model","tool","framework","product"],"link_roles":["pretraining","training","finetuning","evaluation","benchmark"],"modalities":["histopathology","radiology-ct","radiology-mri","radiology-xray","mammography","pet","ultrasound","dermoscopy","endoscopy","genomics","transcriptomics","single-cell","proteomics","protein-sequence","molecules","clinical-text","literature","ehr","multimodal","immunopeptidomics"],"need_status":["open","in-progress","solved"],"openness":["open-weights","gated-weights","api-only","closed"],"regulatory":["research-only","fda-cleared","fda-de-novo","fda-pma","ce-marked","ce-ivdr","not-applicable"],"settings":["basic-research","screening","diagnosis","prognosis","treatment-planning","treatment-response","drug-discovery","clinical-trials","education","vaccine-design","immunotherapy"],"tasks":["feature-extraction","classification","segmentation","detection","screening","risk-prediction","prognosis","treatment-response","survival-analysis","image-text-retrieval","report-generation","question-answering","information-extraction","clinical-trial-matching","protein-structure","variant-effect","gene-expression","single-cell","drug-discovery","drug-repurposing","peptide-mhc-binding","antigen-presentation","neoantigen-prioritisation"]}}