基于语言模型的BRAD数字生物学研究
Language Model Powered Digital Biology with BRAD
AI总结：
针对生物信息学中多类工具、数据库与文献整合难的问题，研究提出原型系统BRAD，这一由LLM驱动的Python智能体可整合多类生物信息学资源，支持多种任务，具备上下文感知的半自主能力，还配有GUI界面。
摘要：
大语言模型（LLMs）的最新进展正在变革生物学、计算机科学、工程学和日常生活。然而，整合各类计算工具、数据库和科学文献仍是生物学研究面临的一大挑战。LLMs非常适合非结构化整合、高效信息检索，以及从这些多元资源中自动化标准工作流和操作。为在生物信息学领域利用这些能力，我们提出了原型系统Bioinformatics Retrieval Augmented Digital assistant（BRAD，生物信息学检索增强数字助手）。BRAD是一款整合了多种生物信息学工具的聊天机器人与智能体系统。该Python包实现了一个由LLMs驱动的AI \texttt{Agent}（智能体），可连接本地文件系统、在线数据库和用户软件。该\texttt{Agent}高度可配置，支持检索增强生成、生物信息学数据库跨库搜索、软件流水线执行等任务。BRAD对生物信息学工具的协同整合打造了一个具备上下文感知能力的半自主系统，其能力超越了传统的基于LLM的聊天机器人。系统还配备图形用户界面（GUI），提供直观的操作入口。
英文摘要：
Recent advancements in Large Language Models (LLMs) are transforming biology, computer science, engineering, and every day life. However, integrating the wide array of computational tools, databases, and scientific literature continues to pose a challenge to biological research. LLMs are well-suited for unstructured integration, efficient information retrieval, and automating standard workflows and actions from these diverse resources. To harness these capabilities in bioinformatics, we present a prototype Bioinformatics Retrieval Augmented Digital assistant (BRAD). BRAD is a chatbot and agentic system that integrates a variety of bioinformatics tools. The Python package implements an AI \texttt{Agent} that is powered by LLMs and connects to a local file system, online databases, and a user's software. The \texttt{Agent} is highly configurable, enabling tasks such as Retrieval-Augmented Generation, searches across bioinformatics databases, and the execution of software pipelines. BRAD's coordinated integration of bioinformatics tools delivers a context-aware and semi-autonomous system that extends beyond the capabilities of conventional LLM-based chatbots. A graphical user interface (GUI) provides an intuitive interface to the system.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
