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ANN Based Classification of Unknown Genome Fragments Using Chaos Game Representation

机译:基于ANN基于未知基因组片段使用混沌游戏表示的分类

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Classification of organisms into different categories using their genomic sequences has found importance in study of evolutionary characteristics, specific identification of previously unknown organisms, study of mutual relationships between organisms and many other aspects in the study of living things. Chaos game representation (CGR) uniquely represents DNA sequences and reveals hidden patterns in it. Frequency-CGR (FCGR) derived from CGR, shows the frequency of sub-sequences present in the DNA sequence. In this paper, a novel method for classification of organisms based on a combination of FCGR and Artificial Neural network (ANN) is proposed. Eight categories from the taxonomical distribution of Eukaryotic organisms are taken and ANN is used for classification. Different configurations of ANN are tested and good accuracy is obtained. The way the fractal nature of DNA helps in classification, is also investigated.
机译:使用其基因组序列对不同类别进行生物体的分类在研究进化特征的研究中,对先前未知的生物体的特异性鉴定,有机体之间的相互关系以及生物研究中的许多其他方面的研究。 Chaos游戏表示(CGR)独特地代表DNA序列,并揭示了它的隐藏模式。 源自CGR的频率CGR(FCGR)显示DNA序列中存在的子序列的频率。 本文提出了一种基于FCGR和人工神经网络(ANN)组合的生物体分类的新方法。 采取了来自真核生物的分类分布的八种类别,ANN用于分类。 测试不同的ANN配置,获得良好的精度。 还研究了DNA分形的分形性质的方式。

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