[论文] BaseCamp --- An Agentic AI Framework for Automating DNA Sequencing Dat...

论文概要

研究领域: ML
作者: Eranga Bandara, Xueping Liang, Asanga Gunaratna
发布时间: 2026-09-26
arXiv: 2609.24309

中文摘要

DNA 测序流程——涵盖质量控制、比对、变异检测和注释——如今已能由工作流管理系统可靠地大规模编排执行。仍然是手动的部分在于围绕执行层的决策层：选择适合样本和平台的质量阈值、裁决边界变异检测、诊断异常，以及确定哪些发现需要专家审查。这些决策重复性强、需要密集判断、在不同操作员之间不一致，且经常未被记录。本文介绍 BaseCamp，一种用于自动化 DNA 测序流程决策层的新型智能体 AI 框架。该框架将流程分解为六个专门的 AI 智能体，覆盖样本接收和质量控制、比对、变异检测、注释、跨阶段监控和报告。关键的是，BaseCamp 的智能体不执行序列分析：成熟的工具执行比对、检测和注释，而智能体在它们之间进行选择、配置它们、解读输出并决定后续步骤。这将语言模型推理限制在其可靠的判断层，同时保留了现有工具保证的可复现性。智能体推理由一个经过微调的领域专业化大语言模型联盟驱动，由中央推理 LLM 协调，在本地执行——测序数据不会离开操作环境——在人机协作编排下运行。

原文摘要

DNA sequencing pipelines, spanning quality control, alignment, variant calling, and annotation, are now reliably executed by workflow management systems that orchestrate established bioinformatics tools at scale. What remains manual is the decision layer surrounding that execution: selecting quality thresholds appropriate to a sample and platform, adjudicating borderline variant calls, diagnosing anomalies, and determining which findings warrant expert review. These decisions are repetitive, judgment-intensive, inconsistent across operators, and frequently undocumented. This paper introduces BaseCamp, a novel agentic AI framework for automating the decision layer of DNA sequencing pipelines. The framework decomposes the pipeline into six specialized AI agents, covering sample intake and qu...

自动采集于 2026-09-27

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