GPT-Rosalind智能体32分钟分析小鼠脑图谱
OpenAI、PerturbAI与斯克里普斯研究所使用1,946个GPT-Rosalind智能体分析覆盖数百万个小鼠脑细胞的全脑CRISPR图谱,据报道耗时32分钟。分散式智能体将基因扰动与科学文献联系起来,提出涉及Tsc1、Tsc2和DCTN1的研究线索;盲评中专家有75%的时间更偏好多智能体报告。不过,相关bioRxiv预印本尚未经过同行评审,生物学假说仍需实验室验证。
公开的Reasoning Atlas和预印本展示了多智能体在加速生物学分析与文献关联方面的实际应用,但专家更偏好报告并不等于所提出的疾病机制已被证实。
What if scientists could uncover new clues about Alzheimer’s and Parkinson’s in minutes instead of months? Working together, OpenAI, PerturbAI(opens in a new window), and Scripps Research(opens in a new window) used thousands of AI agents powered by GPT‑Rosalind(opens in a new window) to analyze and interpret existing experimental data from millions of mouse brain cells(opens in a new window) in just 32 minutes. The agents connected the effects of gene disruptions with findings from scientific literature, uncovering unexpected biological connections that can help scientists understand disease and identify research directions for new treatments. The work shows how AI can help researchers explore more of what large biological experiments reveal.
Modern experiments generate far more data than scientists can thoroughly investigate. Researchers can now alter thousands of genes and measure their effects across millions of cells. But understanding what these results mean for human disease requires connecting complex experimental findings with decades of scattered scientific knowledge. This is where AI can help scientists uncover promising leads that might otherwise be missed.
“We build cell atlases so that other scientists can make discoveries we haven’t imagined yet. AI could help more researchers explore these resources and turn unexpected observations into new questions to test.”
#OpenAI#PerturbAI#Scripps Research#GPT-Rosalind#Reasoning Atlas