Sun Lei, Liu Hui, Zhang Lin, Meng Jia
School of Information Engineering, Yangzhou University, Yangzhou, Jiangsu Province, China; Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, Jiangsu Province, China.
School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou, JiangSu Province, China.
PLoS One. 2015 Oct 5;10(10):e0139654. doi: 10.1371/journal.pone.0139654. eCollection 2015.
Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biological study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones (PCTs). As various information and data about lncRNAs are preserved by previous studies, it is appealing to develop novel methods to identify the lncRNAs more accurately. Our method lncRScan-SVM aims at classifying PCTs and LNCTs using support vector machine (SVM). The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. By integrating features derived from gene structure, transcript sequence, potential codon sequence and conservation, lncRScan-SVM outperforms other approaches, which is evaluated by several criteria such as sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC) and area under curve (AUC). In addition, several known human lncRNA datasets were assessed using lncRScan-SVM. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.
功能性长链非编码RNA（lncRNA）为生物学研究带来了新的见解，然而，要准确区分lncRNA转录本（LNCT）和蛋白质编码转录本（PCT）并非易事。由于先前的研究保留了各种关于lncRNA的信息和数据，因此开发更准确识别lncRNA的新方法很有吸引力。我们的方法lncRScan-SVM旨在使用支持向量机（SVM）对PCT和LNCT进行分类。lncRScan-SVM模型训练、lncRNA预测和方法比较的金标准数据集分别根据人类和小鼠的GENCODE基因注释构建。通过整合来自基因结构、转录本序列、潜在密码子序列和保守性的特征，lncRScan-SVM优于其他方法，这是通过敏感性、特异性、准确性、马修斯相关系数（MCC）和曲线下面积（AUC）等几个标准进行评估的。此外，使用lncRScan-SVM评估了几个已知的人类lncRNA数据集。lncRScan-SVM是预测lncRNA的有效工具，对当前的lncRNA研究非常有用。
