Unlocking human immune system complexity through AI

IF 36.1 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods Pub Date : 2024-08-09 DOI:10.1038/s41592-024-02351-1

Eloise Berson, Philip Chung, Camilo Espinosa, Thomas J. Montine, Nima Aghaeepour

引用次数: 0

Abstract

Advancements in artificial intelligence (AI) have led to unprecedented success in modeling technically challenging domains including language, audio, image and video understanding. Here we discuss the opportunities represented by recent AI methods to advance immunology research.

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通过人工智能解开人类免疫系统的复杂性。

人工智能（AI）技术的进步使我们在语言、音频、图像和视频理解等具有技术挑战性的领域建模取得了前所未有的成功。在此，我们将讨论最新的人工智能方法为推动免疫学研究带来的机遇。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.