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从单分子追踪数据中提取细胞内扩散状态和转移速率。

Extracting intracellular diffusive states and transition rates from single-molecule tracking data.

机构信息

Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.

出版信息

Nat Methods. 2013 Mar;10(3):265-9. doi: 10.1038/nmeth.2367. Epub 2013 Feb 10.

Abstract

We provide an analytical tool based on a variational Bayesian treatment of hidden Markov models to combine the information from thousands of short single-molecule trajectories of intracellularly diffusing proteins. The method identifies the number of diffusive states and the state transition rates. Using this method we have created an objective interaction map for Hfq, a protein that mediates interactions between small regulatory RNAs and their mRNA targets.

摘要

我们提供了一种基于隐马尔可夫模型变分贝叶斯处理的分析工具,用于整合来自数千个细胞内扩散蛋白的短单分子轨迹的信息。该方法可识别扩散状态的数量和状态转移速率。使用这种方法,我们为 Hfq 创建了一个客观的相互作用图谱,Hfq 是一种介导小调控 RNA 与其 mRNA 靶标相互作用的蛋白质。

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