相关实验视频

Updated: Sep 17, 2025

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

对于RNA设计,机器学习以及其他领域的综合数据集

Jan Badura¹, Agnieszka Rybarczyk^1,2, Tomasz Zok³

¹Institute of Computing Science, Poznan University of Technology, 60-965, Poznan, Poland.

Scientific reports

|July 2, 2025

概括

研究人员开发了一个大型,经过验证的数据集,用于对RNA设计和建模算法进行基准测试. 本资源旨在改善RNA二次结构预测和序列设计,这对医学和生物技术至关重要.

科学领域:

计算生物学计算生物学
分子生物学分子生物学
生物信息学是一种生物信息学.

背景情况:

RNA分子调节关键的生物过程,如基因表达和细胞分化.
准确预测RNA二次结构和序列设计是重要的计算挑战.
目前用于RNA预测的现有机器学习方法需要高质量的训练数据,这是目前缺乏的.

研究的目的:

为RNA设计和建模算法建立一个标准化,社区范围的基准数据集.
为了解决缺乏高质量的,经过实验验证的数据,用于培训和评估RNA工具.
为了促进RNA二次结构预测和序列设计的进步.

主要方法:

从经过实验验证的来源编制了一个包含超过32万个实例的综合数据集.
利用数据集来评估最先进的RNA反折叠算法的性能.
对新的基准测试了几个流行的开源RNA设计算法.

主要成果:

数据集包括许多具有挑战性的RNA结构,当前的算法显示的精度不同.
性能评估揭示了复杂结构上现有的RNA设计工具的局限性.
证明了数据集在训练机器学习模型中的实用性,包括RNA序列和结构.

结论:

创建的数据集是RNA计算生物学社区的重要基准.
这个资源有可能显著改善RNA设计和二次结构预测能力.
在这些数据上训练的未来机器学习模型可能会导致基于RNA的应用中的突破.

关键词:

数据集数据集数据集机器学习机器学习多循环多环的方法设计RNA设计RNA设计结构 RNA 结构 RNA 结构在N-way交叉口的交叉点.

更多相关视频

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

A Bioinformatics Pipeline for Investigating Molecular Evolution and Gene Expression using RNA-seq

Published on: May 28, 2021

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Published on: June 8, 2020

相关概念视频

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

Ribosome Profiling

Ribosome Profiling

Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...