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Low-pass frequency-domain filtering of oligonucleotide microarray data images

机译:寡核苷酸微阵列数据图像的低通频域滤波

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Oligonudeotide microarrays technologies offer the possibility of simultaneously monitoring thousands of hybridization reactions. These arrays show high potential for many medical and scientific applications as gene expression monitoring, sequence analysis, and genotyping. Nevertheless microarrays are exposed to errors during manufacturing, similar to silicon circuit electronics and the hybridization process may be contaminated by different reasons. Other source of errors is due to optical noise during scanning and processing, or to interactions between molecular structures and light (dispersion among others). To reduce some of these effects are used replicates of experiments with the cost of increasing expenses. In order to detect noise contamination in microarray data images well-known computational techniques are proposed to help in visual analysis. Some experiments are shown to check the effectiveness of these approaches.
机译:寡核苷酸芯片技术提供了同时监测数千个杂交反应的可能性。这些阵列在基因表达监测,序列分析和基因分型等许多医学和科学应用中显示出很高的潜力。然而,类似于硅电路电子器件,微阵列在制造过程中容易出错,并且杂交过程可能由于不同的原因而受到污染。错误的其他来源是由于扫描和处理过程中的光学噪声,或者是由于分子结构与光之间的相互作用(其中包括色散)。为了减少其中一些影响,使用了重复实验,但增加了费用。为了检测微阵列数据图像中的噪声污染,提出了众所周知的计算技术以帮助进行视觉分析。一些实验表明可以检查这些方法的有效性。

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