Year: 2025
Type: preprint
Abstract: Large language models (LLMs) are transforming cellular biology by enabling the development of "virtual cells"--computational systems that represent, predict, and reason about cellular states and behaviors. This work provides a comprehensive review of LLMs for virtual cell modeling. We propose a unified taxonomy that organizes existing methods into two paradigms: LLMs as Oracles, for direct cellular modeling, and LLMs as Agents, for orchestrating complex scientific tasks. We identify three core tasks--cellular representation, perturbation prediction, and gene regulation inference--and review their associated models, datasets, evaluation benchmarks, as well as the critical challenges in scalability, generalizability, and interpretability.
Source: arXiv (Cornell University)
Authors: Li, Krinos, Xiao, Xianglu, Deng, Shenglong, He, Lucas, Zhong, Zijun, Zou, Yuanjie, Zhan, Zhonghao, Hui, Zheng, Bao, Weiye, Yang, Guang
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4416398238
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