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Biological Sequence Mining Using Plausible Neural Network and its Application to Exon/intron Boundaries Prediction

机译:使用合理的神经网络的生物序列挖掘及其在外显子/内部边界预测中的应用

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Biological sequence usually contains yet to find knowledge, and mining biological sequences usually involves a huge dataset and long computation time. Common tasks for biological sequence mining are pattern discovery, classification and clustering. The newly developed model, Plausible Neural Network (PNN), provides an intuitive and unified architecture for such a large dataset analysis. This paper introduces the basic concepts of the PNN, and explains how it is applied to biological sequence mining. The specific task of biological sequence mining, exon/intron prediction, is implemented by using PNN. The experimental results show the capability of solving biological sequence mining tasks using PNN.
机译:生物序列通常含有尚不寻求知识,并且采矿生物序列通常涉及巨大的数据集和长计算时间。生物序列挖掘的常见任务是模式发现,分类和聚类。新开发的模型,合理的神经网络(PNN),为这种大型数据集分析提供了直观和统一的架构。本文介绍了PNN的基本概念,并解释了它如何应用于生物序列挖掘。通过使用PNN来实施生物序列挖掘,外显子/内含子预测的具体任务。实验结果表明,使用PNN解决生物序列采矿任务的能力。

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