计算机与数字工程2025，Vol.53Issue(3)：781-785,5.DOI:10.3969/j.issn.1672-9722.2025.03.029
基于Conv-Transformer的RNA碱基配对概率预测
RNA Base Pair Probability Prediction Based on Conv-Transformer
摘要
Abstract
RNA base pairing probability measures whether the RNA sequence can form stable base pairs at various points,which is an important attribute of RNA structure and can be used in mRNA vaccine sequence design,disease diagnosis,drug re-search and development and other fields.Therefore,a Conv-Transformer model is proposed to predict the probability of RNA base pairing.Transformer model is used to describe the global characteristics of RNA bases and 1D convolution is used to describe the lo-cal characteristics of RNA bases.Firstly,the global information of RNA bases is extracted by using Attention.Then,the output ma-trix of the Decoder is input to the 1D convolution to extract the local information of RNA bases.Finally,the pairing probabilities of RNA sequence bases are output from the 1D convolution.Root mean square error and the average absolute error are used as perfor-mance evaluation indicators.Experimental results show that the Conv-Transformer model proposed has better performance than the classical machine learning model,with the root mean square error reduced by about 16%and the average absolute error by about 20%.关键词
RNA碱基配对概率/一维卷积/Transformer/幂归一化/多头自注意力/RNA结构预测/深度学习Key words
RNA base pair probability/1D Convolution/Transformer/batchnormalization/multi-head self-attention/RNA structure prediction/deep learning分类
信息技术与安全科学引用本文复制引用
李大舟,陈梅,高巍..基于Conv-Transformer的RNA碱基配对概率预测[J].计算机与数字工程,2025,53(3):781-785,5.基金项目
辽宁省教育厅科学研究项目(编号:LJKZ0449,LJ2020033)资助. （编号:LJKZ0449,LJ2020033）
