Ekimler Semih, Sahin Kaniye
Molecular Biology and Genetics Department, Faculty of Science, Istanbul University, Vezneciler Fatih, 34134 Istanbul, Turkey.
Genes (Basel). 2014 Aug 22;5(3):671-83. doi: 10.3390/genes5030671.
MicroRNAs (miRNAs) have been identified as one of the most important molecules that regulate gene expression in various organisms. miRNAs are short, 21-23 nucleotide-long, single stranded RNA molecules that bind to 3' untranslated regions (3' UTRs) of their target mRNAs. In general, they silence the expression of their target genes via degradation of the mRNA or by translational repression. The expression of miRNAs, on the other hand, also varies in different tissues based on their functions. It is significantly important to predict the targets of miRNAs by computational approaches to understand their effects on the regulation of gene expression. Various computational methods have been generated for miRNA target prediction but the resulting lists of candidate target genes from different algorithms often do not overlap. It is crucial to adjust the bioinformatics tools for more accurate predictions as it is equally important to validate the predicted target genes experimentally.
微小RNA（miRNA）已被确定为调节各种生物体基因表达的最重要分子之一。miRNA是短的、长度为21 - 23个核苷酸的单链RNA分子，它们与靶mRNA的3'非翻译区（3'UTR）结合。一般来说，它们通过mRNA的降解或翻译抑制来沉默靶基因的表达。另一方面，miRNA的表达也因其功能不同而在不同组织中有所差异。通过计算方法预测miRNA的靶标对于理解它们对基因表达调控的影响非常重要。已经产生了各种用于miRNA靶标预测的计算方法，但不同算法得出的候选靶基因列表往往不重叠。调整生物信息学工具以进行更准确的预测至关重要，因为通过实验验证预测的靶基因同样重要。
