DrForna:同转录折叠的可视化。

IF 4.4 3区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Bioinformatics Pub Date : 2023-09-02 DOI:10.1093/bioinformatics/btad555
Anda Ramona Tănasie, Peter Kerpedjiev, Stefan Hammer, Stefan Badelt
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引用次数: 0

摘要

动机从二级结构的层面了解 RNA 折叠,可以深入了解分子的功能。我们有兴趣了解二级结构在转录过程中是如何动态变化的,以及特定的二级结构是在转录过程中已经形成还是仅在转录后才形成。虽然有不同的方法可以模拟共转录折叠,但目前的可视化策略还比较落后。我们需要新的、更合适的方法来帮助探索共转录折叠模拟生成的数据:我们介绍了 DrForna,这是一款用于查看共转录 RNA 折叠模拟时间过程的交互式可视化应用程序。具体来说,用户可以沿时间轴滚动,查看任何特定时间点的结构群:DrForna 是一个 JavaScript 项目,可在 Github https://github.com/ViennaRNA/drforna 上获取,并已部署在 https://viennarna.github.io/drforna 上。
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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DrForna: visualization of cotranscriptional folding.

Motivation: Understanding RNA folding at the level of secondary structures can give important insights concerning the function of a molecule. We are interested to learn how secondary structures change dynamically during transcription, as well as whether particular secondary structures form already during or only after transcription. While different approaches exist to simulate cotranscriptional folding, the current strategies for visualization are lagging behind. New, more suitable approaches are necessary to help with exploring the generated data from cotranscriptional folding simulations.

Results: We present DrForna, an interactive visualization app for viewing the time course of a cotranscriptional RNA folding simulation. Specifically, users can scroll along the time axis and see the population of structures that are present at any particular time point.

Availability and implementation: DrForna is a JavaScript project available on Github at https://github.com/ViennaRNA/drforna and deployed at https://viennarna.github.io/drforna.

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来源期刊
Bioinformatics
Bioinformatics 生物-生化研究方法
CiteScore
11.20
自引率
5.20%
发文量
753
审稿时长
2.1 months
期刊介绍: The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.
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