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

机译:合理神经网络的生物序列挖掘及其在外显子/内含子边界预测中的应用

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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:生物序列通常包含尚未发现的知识,而挖掘生物序列通常涉及庞大的数据集和较长的计算时间。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,似然神经网络(PNN),为如此大的数据集分析提供了直观而统一的体系结构。本文介绍了PNN的基本概念,并解释了如何将其应用于生物序列挖掘。生物序列挖掘的特定任务,即外显子/内含子预测,是通过使用PNN来实现的。实验结果表明了使用PNN解决生物序列挖掘任务的能力

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