MicroRNAs and complex diseases: from experimental results to computational models
MicroRNAs and complex diseases: from experimental results to computational models
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DOI：
10.1093/bib/bbx130
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发表时间：
2019-03-01
影响因子：
9.5
通讯作者：
You, Zhu-Hong
中科院分区：
文献类型：
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作者：
Chen, Xing;Xie, Di;You, Zhu-Hong
在植物、绿色藻类、病毒和动物中发现了大量的microRNA（miRNAs）。作为细胞中最重要的组成部分之一，miRNAs在各种重要的生物学过程中发挥着越来越重要的作用。近几十年来，大量的实验方法和计算模型已经被设计和实施，以确定新的miRNA与疾病的关联。本文就miRNA的功能、miRNA与靶点的相互作用、miRNA与疾病的关系以及一些重要的miRNA相关数据库作一综述。特别地，考虑到越来越多的miRNA与疾病的关联已被实验证实这一重要事实，我们选择了五种重要的miRNA相关的人类疾病和五种关键的疾病相关的miRNA，并提供了相应的介绍。识别与疾病相关的miRNAs已成为生物医学研究的重要目标，这将加速在分子水平上理解疾病的发病机制，并为疾病的诊断、治疗和预防设计分子工具。计算模型已经成为新的miRNA-疾病关联鉴定的重要手段，它可以选择最有希望的miRNA-疾病对进行实验验证，显著减少生物学实验的时间和成本。在这里，我们从不同的角度回顾了20种预测miRNA与疾病相关性的最先进的计算模型。最后，总结了导致预测潜在疾病相关miRNAs困难的4个重要因素、构建预测潜在miRNAs-疾病关联的计算模型的框架（包括5个可行且重要的研究模式）以及计算模型的进一步发展方向。
Plenty of microRNAs (miRNAs) were discovered at a rapid pace in plants, green algae, viruses and animals. As one of the most important components in the cell, miRNAs play a growing important role in various essential and important biological processes. For the recent few decades, amounts of experimental methods and computational models have been designed and implemented to identify novel miRNA-disease associations. In this review, the functions of miRNAs, miRNA-target interactions, miRNA-disease associations and some important publicly available miRNA-related databases were discussed in detail. Specially, considering the important fact that an increasing number of miRNA-disease associations have been experimentally confirmed, we selected five important miRNA-related human diseases and five crucial disease-related miRNAs and provided corresponding introductions. Identifying disease-related miRNAs has become an important goal of biomedical research, which will accelerate the understanding of disease pathogenesis at the molecular level and molecular tools design for disease diagnosis, treatment and prevention. Computational models have become an important means for novel miRNA-disease association identification, which could select the most promising miRNA-disease pairs for experimental validation and significantly reduce the time and cost of the biological experiments. Here, we reviewed 20 state-of-the-art computational models of predicting miRNA-disease associations from different perspectives. Finally, we summarized four important factors for the difficulties of predicting potential disease-related miRNAs, the framework of constructing powerful computational models to predict potential miRNA-disease associations including five feasible and important research schemas, and future directions for further development of computational models.