by mcgilldinglab · Agent Tool · ★ 39
CellAgentChat Overview CellAgentChat constitutes a comprehensive framework integrating gene expression data and existing knowledge of signaling ligand-receptor interactions to compute the probabilities of cell-cell communication. Utilizing the principles of agent-based modeling (ABM), we characterize each cell agent through various attributes, including cell identities (e.g. cell type or clusters), gene expression profiles, ligand-receptor universe and spatial coordinates (optional).
| Stars | 39 |
| Forks | 6 |
| Language | Jupyter Notebook |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.9832797038402/100 |
| Open Issues | 1 |
| Last Updated | 2026-05-31 |
| Created | 2023-06-29 |
| Est. Tokens | ~2814k |
These tools work well together with CellAgentChat for enhanced workflows:
Explore other popular agent tool tools:
CellAgentChat is Python agent-based model tool for inference, visualization and analysis of cell-cell communication from single-cell data. It is categorized as a Agent Tool with 39 GitHub stars.
CellAgentChat is primarily written in Jupyter Notebook.
You can find installation instructions and usage details in the CellAgentChat GitHub repository at github.com/mcgilldinglab/CellAgentChat. The project has 39 stars and 6 forks, indicating an active community.
CellAgentChat is released under the MIT license, making it free to use and modify according to the license terms.