3plex Web: RNA:DNA三联体预测和分析的互动平台。

IF 4.4 2区 生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Computational and structural biotechnology journal Pub Date : 2025-07-14 eCollection Date: 2025-01-01 DOI:10.1016/j.csbj.2025.07.005
Marco Masera, Chiara Cicconetti, Francesca Ferrero, Salvatore Oliviero, Ivan Molineris
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引用次数: 0

摘要

长链非编码rna (lncRNAs)通过与其他分子(包括蛋白质和DNA)合作来发挥其功能。通过单链RNA (ssRNA)和双链DNA (dsDNA)相互作用形成的三链,一直被描述为一种允许lncrna靶向体内特定基因组序列的机制。在计算工具3plex的基础上,我们开发了3plex Web,这是一个可访问的平台,通过集成交互式可视化,统计评估和用户友好的下游分析工作流程来增强RNA:DNA三重结构的预测。3plex Web实现了一些新特性,例如用于统计评估的输入随机化、用于三重稳定性的交互式概要图绘制以及可定制的DNA结合域(DBD)选择。该平台可以通过PATO进行快速分析,与以前的方法相比,大大减少了处理时间,同时提供Snakemake工作流程来整合基因表达数据并探索lncRNA调控机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3plex Web: An interactive platform for RNA:DNA triplex prediction and analysis.

Long non-coding RNAs (lncRNAs) exert their functions by cooperating with other molecules, including proteins and DNA. Triplexes, formed through the interaction between a single-stranded RNA (ssRNA) and a double-stranded DNA (dsDNA), have been consistently described as a mechanism that allows lncRNAs to target specific genomic sequences in vivo. Building on the computational tool 3plex, we developed 3plex Web, an accessible platform that enhances the prediction of RNA:DNA triplexes by integrating interactive visualization, statistical evaluation, and user-friendly downstream analysis workflows. 3plex Web implements new features such as input randomization for statistical assessments, interactive profile plotting for triplex stability, and customizable DNA Binding Domain (DBD) selection. This platform enables rapid analysis through PATO, substantially reducing processing times compared to previous methods, while offering Snakemake workflows to integrate gene expression data and explore lncRNA regulatory mechanisms.

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来源期刊
Computational and structural biotechnology journal
Computational and structural biotechnology journal Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
9.30
自引率
3.30%
发文量
540
审稿时长
6 weeks
期刊介绍: Computational and Structural Biotechnology Journal (CSBJ) is an online gold open access journal publishing research articles and reviews after full peer review. All articles are published, without barriers to access, immediately upon acceptance. The journal places a strong emphasis on functional and mechanistic understanding of how molecular components in a biological process work together through the application of computational methods. Structural data may provide such insights, but they are not a pre-requisite for publication in the journal. Specific areas of interest include, but are not limited to: Structure and function of proteins, nucleic acids and other macromolecules Structure and function of multi-component complexes Protein folding, processing and degradation Enzymology Computational and structural studies of plant systems Microbial Informatics Genomics Proteomics Metabolomics Algorithms and Hypothesis in Bioinformatics Mathematical and Theoretical Biology Computational Chemistry and Drug Discovery Microscopy and Molecular Imaging Nanotechnology Systems and Synthetic Biology
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