Department of Molecular Biology and Genetics, Izmir Institute of Technology Urla, Turkey.
Front Genet. 2012 Oct 10;3:209. doi: 10.3389/fgene.2012.00209. eCollection 2012.
MicroRNAs are small RNA sequences of 18-24 nucleotides in length, which serve as templates to drive post-transcriptional gene silencing. The canonical microRNA pathway starts with transcription from DNA and is followed by processing via the microprocessor complex, yielding a hairpin structure. Which is then exported into the cytosol where it is processed by Dicer and then incorporated into the RNA-induced silencing complex. All of these biogenesis steps add to the overall specificity of miRNA production and effect. Unfortunately, their modes of action are just beginning to be elucidated and therefore computational prediction algorithms cannot model the process but are usually forced to employ machine learning approaches. This work focuses on ab initio prediction methods throughout; and therefore homology-based miRNA detection methods are not discussed. Current ab initio prediction algorithms, their ties to data mining, and their prediction accuracy are detailed.
微 RNA 是一类长度为 18-24 个核苷酸的小 RNA 序列，作为模板驱动转录后基因沉默。经典的微 RNA 途径始于 DNA 的转录，随后通过微处理器复合物进行加工，产生发夹结构。然后将其输出到细胞质中，在那里它被 Dicer 加工，然后整合到 RNA 诱导的沉默复合物中。所有这些生物发生步骤都增加了 miRNA 产生和效应的整体特异性。不幸的是，它们的作用模式才刚刚开始被阐明，因此计算预测算法不能模拟该过程，但通常被迫采用机器学习方法。这项工作主要集中在从头开始的预测方法上；因此，不讨论基于同源性的 miRNA 检测方法。详细介绍了当前的从头预测算法、它们与数据挖掘的联系以及它们的预测准确性。
