EPISODE · Apr 12, 2026 · 21 MIN
783-药物发现的主动学习转录组框架
from 聊聊Sci
本文介绍了一种名为 DrugReflector 的创新型深度学习框架，旨在通过转录组学数据提升表型药物发现的效率。研究人员利用单细胞 RNA 测序技术捕捉疾病状态与药物干预之间的基因表达差异，构建了一个名为“实验室闭环”的有源强化学习系统。该框架在血液病和肿瘤学领域的实验中表现卓越，其筛选命中率较传统随机方法提高了 10 倍以上。通过将表型测量与转录数据相结合，该模型能够不断优化目标特征并揭示如胆固醇生物合成等此前未被发现的药物靶点。总之，这项技术为复杂疾病的药物筛选提供了一个可扩展且可迭代进化的通用化解决方案。References: DeMeo B, Nesbitt C, Miller S A, et al. Active learning framework leveraging transcriptomics identifies modulators of disease phenotypes[J]. Science, 2025, 390(6776): eadi8577.前往小宇宙评论区与主播互动
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783-药物发现的主动学习转录组框架
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