{"slug":"virtual-cell","tag":"virtual-cell","variants":["virtual-cell"],"description":"Groups, companies, collections and technologies building virtual cell models.","count":17,"kinds":{"institution":2,"company":2,"collection":2,"technology":11},"related":[{"slug":"foundation-model","tag":"foundation-model","shared":10},{"slug":"ai","tag":"ai","shared":4},{"slug":"data","tag":"data","shared":2},{"slug":"benchmark","tag":"benchmark","shared":1}],"records":[{"id":"arc-institute","kind":"institution","name":"Arc Institute","route":"/institutions/arc-institute/","tldr":"The Arc Institute is a well-funded nonprofit research institute building 'virtual cell' AI models and the datasets to train them."},{"id":"yale-school-of-medicine","kind":"institution","name":"Yale School of Medicine / Yale Cancer Center","route":"/institutions/yale-school-of-medicine/","tldr":"Home of the Cell2Sentence single-cell language models built with Google, and an NCI-designated comprehensive cancer centre."},{"id":"vevo-therapeutics","kind":"company","name":"Vevo Therapeutics","route":"/companies/vevo-therapeutics/","tldr":"Produced Tahoe-100M, the largest single-cell drug-perturbation atlas, and trains models on it."},{"id":"chan-zuckerberg-initiative","kind":"company","name":"Chan Zuckerberg Initiative (Biohub)","route":"/companies/chan-zuckerberg-initiative/","tldr":"Funds and builds the Human Cell Atlas infrastructure and the CZI virtual cell models (TranscriptFormer), plus one of the largest nonprofit GPU clusters for biology."},{"id":"tahoe-100m","kind":"collection","name":"Tahoe-100M","route":"/collections/tahoe-100m/","tldr":"Tahoe-100M is the biggest single-cell dataset ever released, built to teach AI how cancer cells respond to drugs."},{"id":"arc-virtual-cell-atlas","kind":"collection","name":"Arc Virtual Cell Atlas","route":"/collections/arc-virtual-cell-atlas/","tldr":"Arc's growing library of cell data, the fuel for virtual cell models."},{"id":"geneformer","kind":"technology","name":"Geneformer","route":"/technologies/geneformer/","status":"emerging","tldr":"Geneformer is a transformer trained on about 30 million single cells that encodes each cell as a ranked list of its genes, so deleting a gene in silico shows which genes matter in a disease. It was the first single-cell foundation model in general use, though benchmarks find only modest gains over linear baselines on some tasks."},{"id":"scgpt","kind":"technology","name":"scGPT","route":"/technologies/scgpt/","status":"emerging","tldr":"A GPT-style model for single-cell data that predicts cell types, perturbation responses, and gene networks."},{"id":"universal-cell-embedding","kind":"technology","name":"Universal Cell Embedding (UCE)","route":"/technologies/universal-cell-embedding/","status":"emerging","tldr":"Universal Cell Embedding maps any cell from any species into one shared space without retraining."},{"id":"scfoundation","kind":"technology","name":"scFoundation (BioMap)","route":"/technologies/scfoundation/","status":"emerging","tldr":"scFoundation is a 100-million-parameter model trained on 50 million cells, from China's BioMap."},{"id":"nicheformer","kind":"technology","name":"Nicheformer (spatial single-cell)","route":"/technologies/nicheformer/","status":"emerging","tldr":"Nicheformer is a model trained on both dissociated and spatial data so it learns how a cell's neighbourhood shapes it."},{"id":"cellfm","kind":"technology","name":"CellFM","route":"/technologies/cellfm/","status":"emerging","tldr":"CellFM is an 800-million-parameter single-cell model trained on 100 million human cells."},{"id":"genept","kind":"technology","name":"GenePT","route":"/technologies/genept/","status":"emerging","tldr":"Uses text embeddings of gene descriptions from a general LLM to represent cells, and performs surprisingly well."},{"id":"c2s-scale","kind":"technology","name":"Cell2Sentence / C2S-Scale (Yale, Google)","route":"/technologies/c2s-scale/","status":"emerging","tldr":"Turns a cell's gene expression into a sentence so a normal language model can reason about it; a 27-billion-parameter version proposed a cancer immunotherapy idea that was confirmed in the lab."},{"id":"state-arc","kind":"technology","name":"State (Arc Institute perturbation model)","route":"/technologies/state-arc/","status":"emerging","tldr":"Predicts how cells will respond to a drug or gene knockout, trained on over 100 million perturbed cells."},{"id":"transcriptformer","kind":"technology","name":"TranscriptFormer and rBio (CZI virtual cell models)","route":"/technologies/transcriptformer/","status":"emerging","tldr":"CZI's open cross-species cell models and a reasoning model trained on them."},{"id":"gears","kind":"technology","name":"GEARS and perturbation prediction benchmarks","route":"/technologies/gears/","status":"emerging","tldr":"GEARS is a graph model predicting the effect of gene knockouts; the perturbation benchmarks around it showed how hard the problem is."}]}