中南民族大学学报（自然科学版）2022，Vol.41Issue(6)：697-705,9.DOI:10.20056/j.cnki.ZNMDZK.20220609
基于ACNN-BLSTM的环状RNA识别
Recognition of circular RNA based on ACNN-BLSTM
摘要
Abstract
Circular RNA（circRNA）is a new type of endogenous non-coding RNA，which exists widely in eukaryotic transcriptome and circular structure is formed by the reverse linkage of 5'-end and 3'-end covalent bonds during splicing process. Over the past two decades，circRNA have been shown to function as miRNA sponges and have been closely associated with cancer in gene regulation. Therefore，detection of circRNA is very important for understanding their biological role and biogenesis. At present，the general method for detecting circRNA relies on high-throughput sequencing （RNA-seq），which detects the reverse splicing sites of RNA in the data. However，due to the low accuracy of recognition and data itself，the results of circRNA are high in false positives and false negatives. Therefore，it is necessary to find a more accurate and faster method to identify circRNA. We use the architecture of asymmetric convolutional neural network （ACNN） and bidirectional short and long time memory network （Bi-LSTM） to recognize circRNA in long non-coding （lncRNA）by using the sequence characteristics of circRNA itself. The experimental results show that the ACNN-BLSTM model proposed is the best among the five models in terms of all aspects of performance indicators and recognition accuracy，and the recognition accuracy reaches more than 90%. Compared with the other four common single neural network models，this method has certain advantages.关键词
环状RNA/非对称卷积神经网络/双向长短时记忆网络/RNA识别Key words
circular RNA/asymmetric convolutional neural networks/bidirectional long short-term memory network/RNA recognition分类
医药卫生引用本文复制引用
程威,王帅,范锦江,彭景,林显光,陈恒玲..基于ACNN-BLSTM的环状RNA识别 [J].中南民族大学学报（自然科学版）,2022,41(6):697-705,9.基金项目
国家自然科学基金资助项目 （）
