利用大型语言模型增强功能基因集分析。

IF 36.1 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods Pub Date : 2024-11-28 DOI:10.1038/s41592-024-02526-w

引用次数: 0

摘要

大型语言模型（llm）作为功能基因组学的助手，为基因集分析提供了新的途径。在我们对五种LLMs的评估中，GPT-4是表现最好的模型，它为基因集生成了共同功能，具有高特异性、可靠的自评估置信度和支持分析，补充了传统的功能富集。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Enhancing functional gene set analysis with large language models

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Enhancing functional gene set analysis with large language models

Large language models (LLMs) demonstrate potential as assistants in functional genomics, offering a new avenue for gene set analysis. In our evaluation of five LLMs, GPT-4 was the top-performing model and generated common functions for gene sets with high specificity, reliable self-assessed confidence and supporting analysis, complementing traditional functional enrichment.

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来源期刊

Nature Methods 生物-生化研究方法

CiteScore

58.70

自引率

1.70%

发文量

326

审稿时长

1 months

期刊介绍： Nature Methods is a monthly journal that focuses on publishing innovative methods and substantial enhancements to fundamental life sciences research techniques. Geared towards a diverse, interdisciplinary readership of researchers in academia and industry engaged in laboratory work, the journal offers new tools for research and emphasizes the immediate practical significance of the featured work. It publishes primary research papers and reviews recent technical and methodological advancements, with a particular interest in primary methods papers relevant to the biological and biomedical sciences. This includes methods rooted in chemistry with practical applications for studying biological problems.