这篇文章介绍了一种名为 Tahoe-x1 (Tx1) 的新型单细胞基础模型系列，参数多达 30 亿，专门用于癌症治疗研究。Tx1 模型使用扰动训练的方法，在包括 Tahoe-100M 在内的大型单细胞转录组数据集上进行预训练，并针对癌症相关任务进行微调。作者通过架构优化和高效的训练策略，显著提高了计算效率，并在预测基因必需性、识别癌症标志基因和预测扰动反应等多个基准测试中达到了最先进的性能。这些结果表明，大规模扰动数据对于开发可概括的、具有转化潜力的单细胞基础模型至关重要。References: Gandhi S, Javadi F, Svensson V, et al. Tahoe-x1: Scaling Perturbation-Trained Single-Cell Foundation Models to 3 Billion Parameters[J]. bioRxiv, 2025: 2025.10. 23.683759.
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