| --- |
| license: mit |
| pretty_name: CELL-FM Virtual OpenCell |
| tags: |
| - biology |
| - microscopy |
| - protein |
| - virtual-staining |
| - opencell |
| size_categories: |
| - 100K<n<1M |
| viewer: false |
| --- |
| |
| # CELL-FM Virtual OpenCell |
|
|
| CELL-FM's virtual staining of 1,276 [OpenCell](https://opencell.sf.czbiohub.org) proteins: |
| fluorescence images generated from each protein's amino-acid sequence alone, in 2D and in 3D. |
|
|
| - Browse them in the **Virtual OpenCell** tab of the demo: [huggingface.co/spaces/BoHuangLab/CELL-FM](https://huggingface.co/spaces/BoHuangLab/CELL-FM) |
| - Model weights: [huggingface.co/BoHuangLab/CELL-FM](https://huggingface.co/BoHuangLab/CELL-FM) |
| - Code: [github.com/BoHuangLab/CELL-FM](https://github.com/BoHuangLab/CELL-FM) |
|
|
| Every image is drawn in the same cell. The nucleus channel is one real OpenCell nucleus, from |
| an ATG7 cell line, shared by every protein; CELL-FM generates the protein channel from the |
| sequence. Differences between proteins therefore come from the sequence, not from the cell, and |
| a protein's samples are independent draws for that same nucleus. |
|
|
| ## Contents |
|
|
| | Path | Files | Each file | |
| |---|---|---| |
| | `OpenCell/virtual_staining/<GENE>/NNNN.tif` | 93,510 (30-215 per protein), 24.6 GB | 2D: `(2, 256, 256)` uint16, channels nucleus, protein | |
| | `OpenCell/virtual_staining_3d/<GENE>/NNNN.tif` | 81,664 (64 per protein), 579 GB | 3D: `(48, 2, 192, 192)` uint16, z first, then nucleus, protein | |
| | `OpenCell/virtual_staining_3d_thumbnails/<GENE>.jpg` | 1,276 | Preview sheet of a protein's 64 3D samples | |
|
|
| - **Proteins.** The 1,276 OpenCell proteins with sequences of at most 2,048 residues; the other |
| 35 of OpenCell's 1,311 are longer and were left out. Folder names are OpenCell gene names. |
| `opencell/vs_genes.csv` in the model repo lists all 1,311 with UniProt and Ensembl |
| identifiers, OpenCell's localization annotations and sequences. |
| - **Numbering.** Each protein's files run from `0001.tif` without gaps, so a sample can be |
| requested by name without listing the repo. |
| - **2D.** Made with `opencell/cellfm_vs.bin` from the model repo. Each protein has as many |
| samples as OpenCell has real 256 x 256 crops of its cell line, so the set mirrors OpenCell's |
| 2D projection crops protein for protein. The shared nucleus is |
| `opencell/vs_anchor_nucleus.npy` in the model repo. `opencell/vs_umap_embedding.npz` holds a |
| UMAP of all 93,510 samples, the map shown in the demo. |
| - **3D.** Made with CELL-FM's 3D model, whose weights are not in the model repo. Each sample is |
| a 48 x 192 x 192 stack centred on the nucleus, so the middle slice (25 of 48) cuts through |
| its centre. The files are ImageJ hyperstacks (48 slices x 2 channels) and open as such in |
| Fiji. The voxel size is not recorded. |
| - **Intensities.** Values are relative, not camera counts: each channel is the model's |
| [-1, 1] range mapped linearly to 0-65535, as `(x + 1) / 2 * 65535`. Rescale each image (for |
| example to its 0.1-99.9 percentiles) before display. |
| - **Thumbnail sheets.** For previews only: each sheet is an 8 x 8 grid of 96 x 96 tiles, sample |
| 1 at top left, showing the middle slice of each 3D sample rendered as in the demo (nucleus |
| blue, protein grey). |
|
|
| ## Usage |
|
|
| ```python |
| from huggingface_hub import hf_hub_download, snapshot_download |
| import tifffile |
| |
| # one 2D sample |
| path = hf_hub_download("BoHuangLab/CELL-FM", "OpenCell/virtual_staining/TOMM20/0001.tif", |
| repo_type="dataset") |
| nucleus, protein = tifffile.imread(path) # each (256, 256) uint16 |
| |
| # all 3D samples of one protein (about 450 MB) |
| root = snapshot_download("BoHuangLab/CELL-FM", repo_type="dataset", |
| allow_patterns="OpenCell/virtual_staining_3d/TOMM20/*") |
| stack = tifffile.imread(f"{root}/OpenCell/virtual_staining_3d/TOMM20/0001.tif") |
| print(stack.shape) # (48, 2, 192, 192): z, channel (nucleus, protein), y, x |
| ``` |
|
|
| The whole 2D set: `hf download BoHuangLab/CELL-FM --repo-type dataset --include "OpenCell/virtual_staining/*"`. |
|
|
| ## Source |
|
|
| The nucleus image and the list of proteins come from OpenCell (Cho et al., *Science* 2022, |
| [opencell.sf.czbiohub.org](https://opencell.sf.czbiohub.org)). The protein images are CELL-FM's |
| predictions, not measurements. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{zheng2026virtual, |
| title = {Virtual experiments bridge sequence and microscopy with generative models}, |
| author = {Zheng, Dihan and Hong, Kibeom and Huang, Bo}, |
| journal = {bioRxiv}, |
| year = {2026}, |
| doi = {10.64898/2026.09.13.751243}, |
| url = {https://www.biorxiv.org/content/10.64898/2026.09.13.751243v1} |
| } |
| ``` |
|
|
