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Obtaining Quality Microarray Data via Image Reconstruction

机译:通过图像重建获取质量微阵列数据

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This paper introduces a novel method for processing spotted microarray images, inspired from image reconstruction. Instead of the usual approach that focuses on the signal when removing the noise, the new method focuses on the noise itself, performing a type of interpolation. By recreating the image of the microarray slide, as it would have been with all the genes removed, the gene rations can be calculated with more precision and less influence from outliers and other artefacts that would normally make the analysis of this data more difficult. The new technique is also beneficial, as it does not rely on the accurate fitting of a region to each gene, with its only requirement being an approximate coordinate. In experiments conducted the new method was tested against one of the mainstream methods of processing spotted microarray images. Our method is shown to produce much less variation in gene measurements. This evidence is supported by clustering results that show a marked improvement in accuracy.
机译:本文介绍了用于处理斑点的微阵列的图像,从图像重构启发的新方法。而不是通常的方法去除噪声时集中在信号,新的方法着重于噪声本身,执行内插类型。通过重新创建微阵列芯片的图像,因为它会一直与全部去掉的基因,该基因口粮可以更精确和异常值和其他文物,通常会做出这个数据的分析更加困难影响较小计算。这项新技术也是有益的,因为它不依赖于每个基因的区域的准确拟合,其唯一的要求是一个近似的坐标。在所进行的实验的新方法针对的处理斑点的微阵列的图像的主流方法之一进行测试。我们的方法被示出,以产生基因测量小得多的变化。这方面的证据是通过聚类结果显示精度显着改善的支持。

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