ArticleNature communications2026
Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling.
Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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
8 citing papers in PubMed.
- A meta-interaction basis for cell-cell communication in tissues.bioRxiv : the preprint server for biology · 2026Article
- spaGFM is a scalable graph foundation model for spatial transcriptomics analyses.Research square · 2026Article
- Counterfactual Diffusion Modeling Enables Spatially Targeted Reprogramming of Tissue Microenvironments.Biology · 2026Article
- Review
- Decoding Treg diversity and dysfunction to advance Treg-based therapies in autoimmune and inflammatory diseases.Frontiers in immunology · 2026Review
- CONCERT predicts niche-aware perturbation responses in spatial transcriptomics.bioRxiv : the preprint server for biology · 2025Article
- Quantifying and interpreting biologically meaningful spatial signatures within tumor microenvironments.NPJ precision oncology · 2025Review
- Machine learning to dissect perturbations in complex cellular systems.Computational and structural biotechnology journal · 2025Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Celcomen leverages a mathematical causality framework to disentangle intra- and inter-cellular gene regulation programs in spatial transcriptomics data through a generative graph neural network. It is a first step towards perturbation models of Virtual Tissues and can generate post-perturbation counterfactual spatial transcriptomics, thereby offering access to experimentally inaccessible samples. We validated its disentanglement, identifiability of causal structure, and counterfactual prediction capabilities through simulations and in clinically relevant human glioblastoma, human fetal spleen, and mouse lung cancer samples. Celcomen provides the means to model disease- and therapy-induced changes allowing for new insights into single-cell spatially resolved tissue responses.
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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.