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A Novel Method for Functional Annotation Prediction Based on Combination of Classification Methods

机译:基于分类方法组合的功能注释预测的一种新方法

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Automated protein function prediction defines the designation of functions of unknown protein functions by using computational methods. This technique is useful to automatically assign gene functional annotations for undefined sequences in next generation genome analysis (NGS). NGS is a popular research method since high-throughput technologies such as DNA sequencing and microarrays have created large sets of genes. These huge sequences have greatly increased the need for analysis. Previous research has been based on the similarities of sequences as this is strongly related to the functional homology. However, this study aimed to designate protein functions by automatically predicting the function of the genome by utilizing InterPro (IPR), which can represent the properties of the protein family and groups of the protein function. Moreover, we used gene ontology (GO), which is the controlled vocabulary used to comprehensively describe the protein function. To define the relationship between IPR and GO terms, three pattern recognition techniques have been employed under different conditions, such as feature selection and weighted value, instead of a binary one.
机译:自动化蛋白质功能预测通过使用计算方法定义未知蛋白质功能功能的指定。该技术可用于自动为下一代基因组分析(NGS)中的未定义序列分配基因功能注释。 NGS是一种流行的研究方法,因为DNA测序和微阵列等高通量技术创造了大量基因。这些巨大的序列大大增加了对分析的需求。以前的研究基于序列的相似之处,因为这与功能性同源有关。然而,本研究旨在通过利用Interpro(IPR)来自动预测基因组的功能来指定蛋白质功能,其可以代表蛋白质家族和蛋白质功能的组的性质。此外,我们使用基因本体(GO),其是用于全面描述蛋白质功能的受控词汇。为了定义IPR和GO术语之间的关系,在不同的条件下采用了三种模式识别技术,例如特征选择和加权值,而不是二进制文件。

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