基于堆叠自动编码器的miRNA-疾病关联预测方法  

miRNA-disease Association Prediction Model Based on Stacked Autoencoder

作　　者：刘丹 赵森 颜志良 赵静 王会青 LIU Dan;ZHAO Sen;YAN Zhi-liang;ZHAO Jing;WANG Hui-qing(College of Information and Computer,Taiyuan University of Technology,Taiyuan 030606,China)

机构地区：[1]太原理工大学信息与计算机学院,太原030606

出　　处：《计算机科学》2021年第10期114-120,共7页Computer Science

基　　金：山西省重点研发计划项目(201903D121151);山西省研究生教育改革课题(2019JG020153)。

摘　　要：作为一类小的非编码RNA,miRNA的异常调控与人类疾病的发生和发展密切相关,研究miRNA与疾病的关联对于了解人类疾病致病机制具有重要意义。机器学习方法被广泛应用于miRNA-疾病关联预测,然而现有方法仅仅考虑了miRNA与疾病相似性网络信息,忽略了相似性网络的拓扑结构。因此,文中提出基于堆叠自动编码器的miRNA-疾病关联预测模型SAEMDA,该模型采用重启随机游走获取miRNA与疾病相似性网络的拓扑结构特征,用堆叠自动编码器提取miRNA与疾病的抽象低维特征,将得到的低维特征输入深度神经网络进行miRNA-疾病关联预测。SAEMDA模型在5折交叉验证中取得了较好的结果,并在结肠癌和肺癌两个案例中进行了验证。在结肠癌的案例中,此模型预测的前50个miRNA-疾病关联中的45个miRNA在数据库中得到了验证;在肺癌的案例中,排名前50的miRNA均在数据库中得到了验证。As a group of small non-coding RNA,the abnormal regulation of miRNA is closely related to the occurrence and deve-lopment of human diseases.The study on the associations between miRNA and disease is important for understanding the pathogenic mechanism of human diseases.Machine learning methods are widely used to predict miRNA-disease associations.However, existing methods only consider the information of miRNA and disease similarity networks, ignoring the topology structure of the similarity networks.Therefore, SAEMDA model based on stacked autoencoder is proposed in this paper, it gets the topological structure features of miRNA and disease similarity networks by restart random walk, obtains the abstract low dimensional features of miRNA and disease by stacked autoencoder, and the low dimensional features are input into deep neural network for miRNA-disease associations prediction.SAEMDA model has achieved great results in 5-fold cross-validation, and it has been validated in cases of colon cancer and lung cancer additionally.As for colon cancer, 45 of the top 50 miRNA-disease associations predicted by this model are verified in the database;and in the cases of lung cancer, all the top 50 miRNAs are verified in the database.

关 键 词：miRNA-疾病关联 相似性网络 拓扑结构 重启随机游走 堆叠自动编码器 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]