计算机科学 ›› 2021, Vol. 48 ›› Issue (10): 114-120.doi: 10.11896/jsjkx.200900169
刘丹, 赵森, 颜志良, 赵静, 王会青
LIU Dan, ZHAO Sen, YAN Zhi-liang, ZHAO Jing, WANG Hui-qing
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。
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