ArticleNature2026
Universal cell embedding provides a foundation model for cell biology.
Article in Nature, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
37 citing papers in PubMed.
- Review
- PHAROS: turning single-cell perturbation models into target-directed drug-combination screens.bioRxiv : the preprint server for biology · 2026Article
- Review
- Article
- Single-Cell and Spatial Omics Technologies in Rice Abiotic Stress Biology: A Methodological Review.International journal of molecular sciences · 2026Review
- Article
- Unify learns cellular evolution with universal multimodal embeddings.Nature communications · 2026Article
- Single-cell foundation modeling with species-native protein tokens links regenerative competence across frog and mouse.bioRxiv : the preprint server for biology · 2026Article
- Synthesizing Mechanistic Hypotheses from Single-Cell Omics via Discretized Feature Attribution and Empirical Language Model Grounding.bioRxiv : the preprint server for biology · 2026Article
- Evaluating the learnability of single-cell large language models on multiple tasks.BMC genomics · 2026Article
- Tissueformer: extending single-cell foundation models to predict population-level phenotypes.BMC bioinformatics · 2026Article
- Progress in the Application of Machine Learning in the Field of Single-Cell and Spatial Transcriptomics.Genes · 2026Review
- Linking rare variants to cell-type function in profound autism with brain transcriptomics and foundation models.Cell genomics · 2026Review
- Temporal AI model predicts drivers of cell state trajectories across human aging.bioRxiv : the preprint server for biology · 2026Article
- Representation learning of single-cell RNA-seq data.RNA (New York, N.Y.) · 2026Review
- Patient-derived lung organoids from bronchoalveolar lavage capture epithelial heterogeneity and disease biology in bronchopulmonary dysplasia.Redox biology · 2026Article
- Parameter-free representations outperform single-cell foundation models on downstream benchmarks.ArXiv · 2026Article
- Parameter-free representations outperform single-cell foundation models on downstream benchmarks.bioRxiv : the preprint server for biology · 2026Article
- Virtual Cells Need Context, Not Just Scale.bioRxiv : the preprint server for biology · 2026Article
- Stack: In-Context Learning of Single-Cell Biology.bioRxiv : the preprint server for biology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Developing a universal representation space for cells that encompasses the tremendous molecular diversity of cell types across species would be transformative for cell biology. Recent work using single-cell transcriptomic approaches to create molecular definitions of cell types in the form of cell atlases has provided the necessary data for such an endeavour
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.