Faculty of Health Sciences, University of Macau, Taipa, Macau S.A.R, China.
Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun, China.
Brief Bioinform. 2019 Sep 27;20(5):1836-1852. doi: 10.1093/bib/bby054.
MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression via recognition of cognate sequences and interference of transcriptional, translational or epigenetic processes. Bioinformatics tools developed for miRNA study include those for miRNA prediction and discovery, structure, analysis and target prediction. We manually curated 95 review papers and ∼1000 miRNA bioinformatics tools published since 2003. We classified and ranked them based on citation number or PageRank score, and then performed network analysis and text mining (TM) to study the miRNA tools development trends. Five key trends were observed: (1) miRNA identification and target prediction have been hot spots in the past decade; (2) manual curation and TM are the main methods for collecting miRNA knowledge from literature; (3) most early tools are well maintained and widely used; (4) classic machine learning methods retain their utility; however, novel ones have begun to emerge; (5) disease-associated miRNA tools are emerging. Our analysis yields significant insight into the past development and future directions of miRNA tools.
微小 RNA(miRNA)是通过识别同源序列并干扰转录、翻译或表观遗传过程来调节基因表达的小非编码 RNA。用于 miRNA 研究的生物信息学工具包括 miRNA 预测和发现、结构、分析和靶标预测工具。我们从 2003 年以来发表的 95 篇综述论文和大约 1000 个 miRNA 生物信息学工具中进行了人工整理。我们根据引用次数或 PageRank 得分对它们进行了分类和排名,然后进行了网络分析和文本挖掘(TM)来研究 miRNA 工具的发展趋势。观察到五个关键趋势:(1)miRNA 的识别和靶标预测是过去十年的热点;(2)人工整理和 TM 是从文献中收集 miRNA 知识的主要方法;(3)大多数早期工具得到了很好的维护和广泛使用;(4)经典的机器学习方法仍然具有实用性,但新方法已经开始出现;(5)与疾病相关的 miRNA 工具正在出现。我们的分析深入了解了 miRNA 工具过去的发展和未来的方向。