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一种评估RNA编码潜力的方法,利用开放式读取和高能级图的相互作用效应来评估RNA的编码潜力

Hua Gao¹, Peng Gao², Ning Ye¹

¹College of Forestry, Nanjing Forestry University, Longpan, Nanjing, 210037, Jiangsu, China; College of Information Science and Technology, Nanjing Forestry University, Longpan, Nanjing, 210037, Jiangsu, China.

Computers in biology and medicine

|November 26, 2023

概括

这项研究引入了一种新的方法,使用序列特征准确区分长非编码RNA (lncRNAs) 和蛋白质编码RNA (pcRNAs). 开发的方法对物种不敏感,绕过了超参数调整的需要,提高了RNA分类的准确性.

科学领域:

生物信息学是一种生物信息学.
分子生物学分子生物学
基因组学就是基因组学.

背景情况:

区分长非编码RNAs (lncRNAs) 和蛋白质编码RNAs (pcRNAs) 对于理解发育和疾病中的基因调节至关重要.
现有的RNA编码潜力评估计算方法依赖于各种序列属性,但往往需要大量调整.

研究的目的:

开发一种新的,准确的,易于应用的方法来区分lncRNAs和pcRNAs.
设计可靠且不需要超参数优化的序列衍生特征.

主要方法:

基于开放式读取 (ORF) 对RNA序列相互作用和位点电强度的影响,设计了一系列功能.
使用这些设计特征构建了一个分类模型.
辅助功能与主要功能相结合,进一步提高了预测准确度.

主要成果:

基于设计特征构建的单一模型实现了强大的分类器性能,准确度在82%至89%之间.
将辅助功能与设计功能相结合,导致预测准确度与最高性能分类工具相当或超过.
开发的方法证明了物种不敏感性,使其在不同的生物体中广泛适用.

结论:

拟议的特征设计和分类方法提供了一个准确和用户友好的方法来区分lncRNAs和pcRNAs.
对物种不敏感性和缺乏超参数调要求,促进了在RNA研究中广泛采用.
识别的特征相关性为未来对RNA编码潜力和功能的研究提供了洞察力.

关键词:

打开阅读框架打开阅读框架预测预测预测蛋白质编码的潜在潜力波浪式的小波段 (wavelet) 是一个小波段.在cnRNA中.

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