{"entity":{"id":"paper-hao-nat-methods","kind":"paper","name":"Large-scale foundation model on single-cell transcriptomics","aka":[],"tldr":"Paper cited by one technology page, indexed on Europe PMC as PubMed record 38844628 and published in Nature methods; the citing page links this DOI, which is how the record was matched.","summary":"Large pretrained models have become foundation models leading to breakthroughs in natural language processing and related fields. Developing foundation models for deciphering the 'languages' of cells and facilitating biomedical research is promising yet challenging. Here we developed a large pretrained model scFoundation, also named 'xTrimoscFoundation α ', with 100 million parameters covering about 20,000 genes, pretrained on over 50 million human single-cell transcriptomic profiles. scFoundation is a large-scale model in terms of the size of trainable parameters, dimensionality of genes and volume of training data. Its asymmetric transformer-like architecture and pretraining task design empower effectively capturing complex context relations among genes in a variety of cell types and states. Experiments showed its merit as a foundation model that achieved state-of-the-art performances in a diverse array of single-cell analysis tasks such as gene expression enhancement, tissue drug response prediction, single-cell drug response classification, single-cell perturbation prediction, cell type annotation and gene module inference.\n\nIndexed on Europe PMC as PubMed record 38844628 (DOI 10.1038/s41592-024-02305-7). Matched by DOI alone: one technology page cites this DOI among its external links (the pages are listed under Related), and this page was written so that the citation resolves inside OnCo. No figure has been checked by an editor.","asOf":"2026-09-22","links":[{"label":"Nat Methods 2024","url":"https://doi.org/10.1038/s41592-024-02305-7"},{"label":"PubMed","url":"https://pubmed.ncbi.nlm.nih.gov/38844628/"},{"label":"Europe PMC","url":"https://europepmc.org/article/MED/38844628"}],"tags":["europepmc-ingest"],"related":["scfoundation"],"cancers":[],"sections":[],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":[],"trials":[],"people":[],"bottlenecks":[],"keyPapers":[],"journals":[],"dependsOn":[],"notes":[],"journal":"Nature methods","year":2024,"doi":"10.1038/s41592-024-02305-7","pmid":"38844628","authors":"Hao M, Gong J, Zeng X, et al.","paperType":"observational","findings":[],"whatItMeans":"One technology page on OnCo cites this paper by its DOI; this record gives the citation a page of its own so a reader can follow it without leaving OnCo. Read the abstract above alongside the citing page listed under Related; the record was created automatically from the Europe PMC entry and its figures have not been checked by hand.","caveats":["Matched to the citing OnCo records by DOI alone; the summary reproduces the Europe PMC abstract and no figure has been verified against the full paper."]},"route":"/key-papers/paper-hao-nat-methods/","neighbours":{"technology":[{"id":"scfoundation","kind":"technology","name":"scFoundation (BioMap)","route":"/technologies/scfoundation/"}]}}