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English(EN) An immune world model for multiscale forecasting and therapeutic hypothesis generation

AI科学家构建免疫世界模型用于多尺度预测

研究人员开发了一个“免疫世界模型”,使用一个受治理的进化AI科学家来预测多尺度免疫反应并生成治疗假设。这个由AI驱动的模型整合了细胞、组织和患者特异性的免疫状态,使其能够预测不同生物学层面的干预结果。该模型成功地泛化到未见的生物学背景和干预措施,并指导分析提出了涉及IL-36γ加SIRPα抑制的新型治疗假设。 AI

影响 该模型通过更准确地预测复杂的生物相互作用,有可能加速药物发现和治疗开发。

排序理由 该条目是一篇学术论文,详细介绍了一个新颖的AI模型及其在科学研究中的应用。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI科学家构建免疫世界模型用于多尺度预测

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该条目是一篇学术论文,详细介绍了一个新颖的AI模型及其在科学研究中的应用。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Taoyong Cui, Xi Wang, Zonghang Li, Jinchao Ding, Lingsen You, Yuzhi Xu, Wanghan Xu, Fang Wu, Kejun Ying, Wanli Ouyang, Pheng Ann Heng, Ling Yang, Zhenfei Yin, Yingcheng Wu ·

    用于多尺度预测和治疗假设生成的免疫世界模型

    arXiv:2609.14709v1 Announce Type: new Abstract: Immune therapies act across cell-intrinsic programs, tissue ecosystems, and patient-specific immune states, yet most predictors address these scales separately. We used a governed evolutionary AI Scientist to construct the Immune Wo…