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0The paper introduces CellForge, an innovative framework that utilizes coordinated teams of autonomous AI agents to completely automate the design and implementation of virtual-cell models. By treating neural network architectures as scientific hypotheses, the system processes diverse single-cell omics data, analyzes biological literature through a critic-mediated discussion protocol, and generates competitive perturbation-prediction models without human design intervention. Through rigorous evaluations on genetic, chemical, and cytokine datasets, the multi-agent system consistently outperforms traditional baselines and produces research plans favored by blinded human experts.
References:
Gerstein M, Tang X, Chen J, et al. AI Scientists for Building Virtual-Cell Models[J]. 2026.
