Accumulating evidences demonstrate that miRNAs can be treated as critical biomarkers in various complex human diseases. Thus, the identifications on potential miRNA-disease associations have become a hotpot for providing better understanding of disease pathology in this field. Recently, with various biological datasets, increasingly computational prediction approaches have been designed to uncover disease-related miRNAs for further experimental validation. To improve the prediction accuracy, several algorithms integrated miRNA similarities of known miRNA-disease associations to enhance the miRNA functional similarity network and disease similarities of known miRNA-disease associations to enhance the disease semantic similarity network. It is anticipated that machine learning methods would become an effective biological resource for clinical experimental guidance.

中文翻译：

---

ES-MDA：基于增强相似性的MiRNA疾病协会。

越来越多的证据表明，miRNA可以作为人类各种复杂疾病中的关键生物标志物。因此，关于潜在的miRNA-疾病关联的鉴定已成为一个热点，可以更好地了解该领域的疾病病理。最近，随着各种生物学数据集的发展，越来越多的计算预测方法被设计用于揭示疾病相关的miRNA，以进行进一步的实验验证。为了提高预测准确性，几种算法集成了已知的miRNA-疾病关联的miRNA相似性以增强miRNA的功能相似性网络和已知的miRNA-疾病关联的疾病相似性以增强疾病的语义相似性网络。