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Paper · 2512.00306 · ICLR · 2025

VCWorld: A Biological World Model for Virtual Cell Simulation

Shuangjia Zheng, Zichen Wang, Zhijian Wei, Runze Ma, Zhongmin Li, Shuotong Song

arXiv · PDF · Open in the Atlas

Code that ran

We lifted 14 functions out of this paper's own repositories and ran 0 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.

RepositoryRoleRan
theislab/cpa canonical 0 of 8
GENTEL-lab/VCWorld canonical 0 of 6
FunctionStatusWhere it lives
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entropy_batch_mixing Not yet run theislab/cpa/cpa/_metrics.py
code served (permissive licence) · get_code("a097de2c5ee5703a")
evaluate_r2_benchmark Not yet run theislab/cpa/cpa/_api.py
code served (permissive licence) · get_code("7884dc6fe2db998a")
fast_dimred Not yet run theislab/cpa/cpa/_plotting.py
code served (permissive licence) · get_code("1d04de8baa8067c6")
get_description Not yet run GENTEL-lab/VCWorld/src/cli_pipeline/stages/prompt.py
pointer only (licence: NONE) · get_code("6d18c722c8734c08")
get_palette Not yet run theislab/cpa/cpa/_plotting.py
code served (permissive licence) · get_code("7c73c81f20db72ff")
get_reference_from_combo Not yet run theislab/cpa/cpa/_api.py
code served (permissive licence) · get_code("04e7a3ac4c778291")
knn_purity Not yet run theislab/cpa/cpa/_metrics.py
code served (permissive licence) · get_code("d20076190239a46e")
linear_interp Not yet run theislab/cpa/cpa/_api.py
code served (permissive licence) · get_code("b74b8f3ae9fbcf97")
load_drug_data Not yet run GENTEL-lab/VCWorld/src/cli_pipeline/stages/retrieve.py
pointer only (licence: NONE) · get_code("2cd78d65a0e02fe4")
load_json Not yet run GENTEL-lab/VCWorld/src/cli_pipeline/stages/prompt.py
pointer only (licence: NONE) · get_code("581e1a3430c33f5f")
load_similarity_json Not yet run GENTEL-lab/VCWorld/src/cli_pipeline/stages/retrieve.py
pointer only (licence: NONE) · get_code("b4c67b07ba135ccc")
load_template_vars Not yet run GENTEL-lab/VCWorld/src/cli_pipeline/stages/prompt.py
pointer only (licence: NONE) · get_code("2f527d54bf7044a8")
log10_with0 Not yet run theislab/cpa/cpa/_plotting.py
code served (permissive licence) · get_code("a2338578129cfbb5")

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Abstract

Virtual cell modeling aims to predict cellular responses to perturbations. Existing virtual cell models rely heavily on large-scale single-cell datasets, learning explicit mappings between gene expression and perturbations. Although recent models attempt to incorporate multi-source biological information, their generalization remains constrained by data quality, coverage, and batch effects. More critically, these models often function as black boxes, offering predictions without interpretability or consistency with biological principles, which undermines their credibility in scientific research. To address these challenges, we present VCWorld, a cell-level white-box simulator that integrates structured biological knowledge with the iterative reasoning capabilities of large language models to instantiate a biological world model. VCWorld operates in a data-efficient manner to reproduce perturbationinduced signaling cascades and generates interpretable, stepwise predictions alongside explicit mechanistic hypotheses. In drug perturbation benchmarks, VCWorld achieves state-of-the-art predictive performance, and the inferred mechanistic pathways are consistent with publicly available biological evidence. Our code is publicly available at https://github.com/GENTEL-lab/VCWorld.

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