Studying RNA dynamics from single-cell RNA sequencing snapshots

IF 36.1 1区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Nature Methods Pub Date : 2024-08-05 DOI:10.1038/s41592-024-02366-8

引用次数: 0

Abstract

Rapid advancements in transcriptomics have enabled the quantification of individual transcripts for thousands of genes in millions of single cells. By coupling a machine learning inference framework with biophysical models describing the RNA life cycle, we can explore the dynamics driving RNA production, processing and degradation across cell types.

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从单细胞 RNA 测序快照中研究 RNA 动态。

转录组学的飞速发展使得对数百万个单细胞中成千上万个基因的单个转录本进行量化成为可能。通过将机器学习推理框架与描述 RNA 生命周期的生物物理模型相结合，我们可以探索驱动跨细胞类型 RNA 生产、加工和降解的动力学。

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.

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