Lingshu-Cell: A generative cellular world model for transcriptome modeling toward virtual cells
Modeling cellular states and predicting their responses to perturbations are central challenges in computational biology and the development of virtual cells. Existing foundation models for single-cell transcriptomics provide powerful static representations, but they do not explicitly model the distribution of cellular states for generative simulation. Here, we introduce Lingshu-Cell, a masked discrete diffusion model that learns transcriptomic state distributions and supports conditional simulation under perturbation. By operating directly in a discrete token space that is compatible with the sparse, non-sequential nature of single-cell transcriptomic data, Lingshu-Cell captures complex ...
| Authors | Han Zhang, Guo-Hua Yuan, Chaohao Yuan et al. |
|---|---|
| Primary category | q-bio.QM |
| Published | 26 March 2026 |
| Last updated at source | 26 March 2026 |
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