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Prediction of novel pre-microRNAs with high accuracy through boosting and SVM

机译:通过Boosting和SVM高精度预测新型pre-microRNA

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High-throughput deep-sequencing technology has generated an unprecedented number of expressed short sequence reads, presenting not only an opportunity but also a challenge for prediction of novel microRNAs. To verify the existence of candidate microRNAs, we have to show that these short sequences can be processed from candidate pre-microRNAs. However, it is laborious and time consuming to verify these using existing experimental techniques. Therefore, here, we describe a new method, miRD, which is constructed using two feature selection strategies based on support vector machines (SVMs) and boosting method. It is a high-efficiency tool for novel pre-microRNA prediction with accuracy up to 94.0% among different species.
机译:高通量深度测序技术已产生了空前数量的表达短序列读段,这不仅为预测新型microRNA提供了机会,而且也带来了挑战。为了验证候选microRNA的存在,我们必须证明可以从候选pre-microRNA处理这些短序列。但是,使用现有的实验技术来验证这些方法既费力又费时。因此,在这里,我们描述了一种新的方法miRD,它是基于支持向量机(SVM)和Boosting方法使用两种特征选择策略构建的。这是一种高效的工具,可用于新颖的预microRNA预测,不同物种间的准确率高达94.0%。

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