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English(EN) Unlocking the Regulatory Genome by ARGUS: An Evidence-Constrained Agentic Framework for Interpreting Single Nucleotide Variants

新的代理框架ARGUS改进了基因组变异解释

研究人员开发了ARGUS,一个旨在改进基因组非编码调控区单核苷酸变异(SNVs)解释的代理框架。与经常产生幻觉或捏造证据的标准大型语言模型不同,ARGUS采用了一种结构化方法。它将确定性的生物计算与LLM介导的推理相结合,使用规划器选择证据来源,并使用验证器解释观察结果,从而减少了不确定性并提高了与疾病相关的变异的功能解释的准确性。 AI

影响 该框架提供了一种更可靠的基因组数据解释方法,通过减少LLM引起的错误,有可能加速个性化医学领域的发现。

排序理由 该集群描述了一种用于解释基因组变异的新研究框架,该框架已作为科学论文发布在arXiv上。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新的代理框架ARGUS改进了基因组变异解释

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该集群描述了一种用于解释基因组变异的新研究框架,该框架已作为科学论文发布在arXiv上。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Pratik Dutta, Matthew B. Obusan, Max Chao, Rekha Sathian, Nimisha Papineni, Ramana V. Davuluri ·

    利用ARGUS解锁监管基因组:一种基于证据约束的代理框架,用于解释单核苷酸变异

    arXiv:2610.12281v1 Announce Type: cross Abstract: Over 90% of disease-associated variants from genome-wide association studies fall in noncoding regulatory regions, yet their functional interpretation remains a central open problem in genomic medicine. Large language models promp…