Neuro-Fuzzy Ensemble Approach for Microarray Cancer Gene Expression Data Analysis

Zhenyu Wang, Vasile Palade, Yong Xu
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引用次数: 90

Abstract

A neuro-fuzzy ensemble model (NFE) is proposed in this paper for analysing the gene expression data from microarray experiments. The proposed approach was tested on three benchmark cancer gene expression data sets. Experimental results show that our NFE model can be used as an efficient computational tool for microarray data analysis. In addition, compared to some most widely used approaches, neuro-fuzzy (NF)-based models not only supply good classification results, but their behavior can also be explained and interpreted in human understandable terms, which provides the researchers with a better understanding of the data
微阵列癌症基因表达数据分析的神经模糊集成方法
本文提出了一种神经模糊集成模型(NFE),用于分析基因芯片实验的基因表达数据。该方法在三个基准癌症基因表达数据集上进行了测试。实验结果表明,NFE模型可以作为微阵列数据分析的有效计算工具。此外,与一些最广泛使用的方法相比,基于神经模糊(NF)的模型不仅提供了良好的分类结果,而且它们的行为也可以用人类可理解的术语来解释和解释,这为研究人员提供了更好的数据理解
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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