Single-cell foundation model
Also known as: foundation model · scFM · foundation cell model
Large pretrained models on single-cell data such as scGPT, Geneformer and scFoundation. Benchmarks in the library report limited zero-shot performance and no reliable gain over simple baselines for perturbation prediction. VC0008 VC0009 VC0011 VC0050
Review pending Version 0.1.0 · status: draft · last expert review: not yet reviewed
Relations
| Subject | Relation | Object | Confidence | Evidence (role) |
|---|---|---|---|---|
| Geneformer | associated with | Single-cell foundation model | high | VC0009 supports From: AI virtual cell models |
| scGPT | associated with | Single-cell foundation model | high | VC0008 supports From: AI virtual cell models |
| scFoundation | associated with | Single-cell foundation model | high | VC0011 supports From: AI virtual cell models |
Appears in research topics
Appears in library items (26)
Items whose title, tags or one-line summary match this entity (derived from the data), plus the items cited as evidence for the description.
- VC0119 NeurIPS 2026 Workshop: Foundation Models for the Brain and Body — NeurIPS, NeurIPS 2026, Sydney, 2026
- VC0056 Systematic evaluation of single-cell foundation model interpretability: attention-derived edge scores add no incremental value over gene-level features for perturbation-target prediction. — Kendiukhov I., BMC genomics, 2026
- VC0112 Lessons from Ron Alfa (Noetik) on AI-native precision oncology — Pear Healthcare Playbook, Substack, 2026
- VC0047 · preprint Cellfm-datasets: A Unified Data Infrastructure for Single-Cell and Spatial Transcriptomics Foundation Model Pretraining — Zhang L, Pang J, Yan J, Tang W, Deng Y, He Y., bioRxiv, 2026
- VC0098 Foundation Model Based on Routine Magnetic Resonance Imaging for Brain Tumor Molecular Profiling and Progression Prediction. — Li J, Liu R, Xing Y, Gao X, Yin Q, Su Q., JCO precision oncology, 2026
- VC0035 · preprint CellFluxV2 : An Image Generative Foundation Model for Virtual Cell Modeling — Zhang Y, Su Y, Wefers Z, Su S, Li H, Li T, Wang C, Burgess J, Lozano A, Zhou L, Ding D, Nirschl J, Lundberg E, Yeung-Levy S., bioRxiv, 2026
- VC0034 · preprint scPRINT-2: Towards the next-generation of cell foundation models and benchmarks — Kalfon J, Peyré G, Cantini L., bioRxiv, 2025
- VC0025 Novae: a graph-based foundation model for spatial transcriptomics data. — Blampey Q, Benkirane H, Bercovici N, Mulder K, Gessain G, Ginhoux F, André F, Cournède PH., Nature methods, 2025
- VC0099 A foundation model for brain tumor MRI analysis: WHO grading and subtype classification. — Li J, Liu R, Xing Y, Gao X, Yin Q, Su Q., Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2025
- VC0028 STPath: a generative foundation model for integrating spatial transcriptomics and whole-slide images. — Huang T, Liu T, Babadi M, Ying R, Jin W., NPJ digital medicine, 2025
- VC0024 Nicheformer: a foundation model for single-cell and spatial omics. — Tejada-Lapuerta A, Schaar AC, Gutgesell R, Palla G, Halle L, Minaeva M, Vornholz L, Dony L, Drummer F, Richter T, Bahrami M, Theis FJ., Nature methods, 2025
- VC0055 · preprint Multimodal Benchmarking of Foundation Model Representations for Cellular Perturbation Response Prediction — Hasanaj E, Cole E, Mohammadi S, Addagudi S, Zhang X, Song L, Xing EP., bioRxiv, 2025
- VC0045 · preprint X-Atlas/Orion: Genome-wide Perturb-seq Datasets via a Scalable Fix-Cryopreserve Platform for Training Dose-Dependent Biological Foundation Models — Huang AC et al., bioRxiv, 2025
- VC0114 Bioptimus: multimodal biology foundation model (NVIDIA compute) — Bioptimus, Bioptimus news, 2025
- VC0026 A visual-omics foundation model to bridge histopathology with spatial transcriptomics. — Chen W et al., Nature methods, 2025
- VC0049 Benchmarking foundation cell models for post-perturbation RNA-seq prediction. — Csendes G, Sanz G, Szalay KZ, Szalai B., BMC genomics, 2025
- VC0050 Zero-shot evaluation reveals limitations of single-cell foundation models. — Kedzierska KZ, Crawford L, Amini AP, Lu AX., Genome biology, 2025
- VC0037 · preprint A perturbation proteomics-based foundation model for virtual cell construction — Sun R, Qian L, Li Y, Cheng H, Xue Z, Zhang X, Tan L, Zhan Y, Hu W, Xiao Q, Liu Z, Zhang G, Weinan E, Zhou P, Wen H, Zhu Y, Guo T., bioRxiv, 2025
- VC0027 · preprint scGPT-spatial: Continual Pretraining of Single-Cell Foundation Model for Spatial Transcriptomics — Wang C, Cui H, Zhang A, Xie R, Goodarzi H, Wang B., bioRxiv, 2025
- VC0029 GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model. — Yang X et al., Cell research, 2024
- VC0051 · preprint PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction — Wenteler A, Occhetta M, Branson N, Curean V, Huebner M, Dee W, Connell W, Chung SP, Hawkins-Hooker A, Ektefaie Y, Valdez Córdova CM, Gallagher-Syed A., bioRxiv, 2024
- VC0011 Large-scale foundation model on single-cell transcriptomics. — Hao M, Gong J, Zeng X, Liu C, Guo Y, Cheng X, Wang T, Ma J, Zhang X, Song L., Nature methods, 2024
- VC0039 Towards a general-purpose foundation model for computational pathology. — Chen RJ et al., Nature medicine, 2024
- VC0008 scGPT: toward building a foundation model for single-cell multi-omics using generative AI. — Cui H, Wang C, Maan H, Pang K, Luo F, Duan N, Wang B., Nature methods, 2024
- VC0012 · preprint Universal Cell Embeddings: A Foundation Model for Cell Biology — Rosen Y, Roohani Y, Agrawal A, Samotorcan L, Tabula Sapiens Consortium, Quake SR, Quake SR, Leskovec J., bioRxiv, 2023
- VC0009 Transfer learning enables predictions in network biology. — Theodoris CV, Xiao L, Chopra A, Chaffin MD, Al Sayed ZR, Hill MC, Mantineo H, Brydon EM, Zeng Z, Liu XS, Ellinor PT., Nature, 2023
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