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MicroRNA prediction with a novel ranking algorithm based on random walks

机译:基于随机游走的新型排名算法预测MicroRNA

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摘要

MicroRNA (miRNAs) play essential roles in post-transcriptional gene regulation in animals and plants. Several existing computational approaches have been developed to complement experimental methods in discovery of miRNAs that express restrictively in specific environmental conditions or cell types. These computational methods require a sufficient number of characterized miRNAs as training samples, and rely on genome annotation to reduce the number of predicted putative miRNAs. However, most sequenced genomes have not been well annotated and many of them have a very few experimentally characterized miRNAs. As a result, the existing methods are not effective or even feasible for identifying miRNAs in these genomes.
机译:MicroRNA(miRNA)在动植物的转录后基因调控中起着至关重要的作用。已经开发了几种现有的计算方法来补充实验方法,以发现在特定环境条件或细胞类型中限制性表达的miRNA。这些计算方法需要足够数量的特征化miRNA作为训练样本,并依靠基因组注释来减少预测的假定miRNA的数量。但是,大多数测序的基因组都没有得到很好的注释,其中许多具有很少的实验表征的miRNA。结果,现有的方法对于鉴定这些基因组中的miRNA是无效或什至不可行的。

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