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Ontology-Based Genes Similarity Calculation with TF-IDF

机译:TF-IDF的基于本体的基因相似度计算

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The Gene Ontology (GO) provides a controlled vocabulary of terms for describing genes from different data resources. In this paper, we proposed a novel method determining semantic similarity of genes based on GO. The key principle of our method relies on the introduction of Term Frequency (TF) and Inverse Document Frequency (IDF) to quantify the weights of different GO terms to the same gene. Different from previous leading methods, our method needs no parameters and computes the gene similarity directly rather than term similarity first. Experimental results of clustering genes in biological pathways from Saccharomyces Genome Database (SGD) have demonstrated that our method is quite competitive and outperforms leading method in certain cases.
机译:基因本体论(GO)提供了可控的词汇表,用于描述来自不同数据资源的基因。在本文中,我们提出了一种新的基于GO的基因语义相似度确定方法。我们方法的关键原理依赖于术语频率(TF)和文档反向频率(IDF)的引入,以量化不同GO术语对同一基因的权重。与以前的领先方法不同,我们的方法不需要任何参数,并且可以直接计算基因相似度,而无需先进行术语相似度计算。来自酿酒酵母基因组数据库(SGD)的生物途径中的基因聚类实验结果表明,在某些情况下,我们的方法具有相当的竞争力,并且优于领先的方法。

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