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A Neuro-Fuzzy Inference System to Infer Gene-Gene Interactions Based on Recognition of Microarray Gene Expression Patterns

机译:基于微阵列基因表达模式识别的基因 - 基因相互作用的神经模糊推理系统

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摘要

A neuro-fuzzy inference system that recognizes the expression patterns of genes in microarray gene expression (MGE) data, called GeneCFE-ANFIS, is proposed to infer gene interactions. In this study, three primary features are utilized to extract genes' expression patterns and used as inputs to neuro-fuzzy inference system. The proposed algorithm learns expression patterns from the known genetic interactions, such as the interactions confirmed by qRT-PCR experiments or collected through text-mining technique by surveying previously published literatures, and then predicts other gene interactions according to the learned patterns. The proposed neuro-fuzzy inference system was applied to a public yeast MGE data set. Two simulations were conducted and checked against 112 pairs of qRT-PCR confirmed gene interactions and 77 TFs pairs collected from literature respectively to evaluate the performance of the proposed algorithm.
机译:提出了一种神经模糊推理系统,其识别出众所周央基因表达(MGE)数据中的基因表达模式,称为GenecFe-Anfis,以推断基因相互作用。在该研究中,利用三个主要特征来提取基因的表达模式并用作神经模糊推理系统的输入。所提出的算法从已知的遗传相互作用中得出表达模式,例如通过测量先前公开的文献通过进行QRT-PCR实验确认的相互作用或通过胸部采矿技术收集,然后根据学习模式预测其他基因相互作用。所提出的神经模糊推理系统应用于公共酵母MGE数据集。进行两次模拟并检查112对QRT-PCR确认的基因相互作用和从文献中收集的77个TFS对,以评估所提出的算法的性能。

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