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过滤和微阵列图像重建通过链式傅立叶噪声

Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers
课程网址: http://videolectures.net/ida07_fraser_nfamir/  
主讲教师: Karl Fraser
开课单位: 布鲁内尔大学
开课时间: 2007-10-08
课程语种: 英语
中文简介: 微阵列允许生物学家同时确定数万个基因的基因表达,然而由于生物过程,所得的微阵列载玻片充满了噪音。在基因表达的定量过程中,为了精确的目的,需要去除基因的噪音或背景。本文介绍了一种用于这种背景去除过程的新技术。该技术使用基因的邻居区域作为代表性背景像素并重建基因区域本身,使得该区域类似于本地背景。通过使用这种新的背景图像,可以更准确地计算基因表达。进行实验以针对主流和替代微阵列分析方法测试该技术。我们的过程被证明可以减少最终表达结果的可变性。
课程简介: Microarrays allow biologists to determine the gene expressions for tens of thousands of genes simultaneously, however due to biological processes, the resulting microarray slides are permeated with noise. During quantification of the gene expressions, there is a need to remove a gene’s noise or background for purposes of precision. This paper presents a novel technique for such a background removal process. The technique uses a gene’s neighbour regions as representative background pixels and reconstructs the gene region itself such that the region resembles the local background. With use of this new background image, the gene expressions can be calculated more accurately. Experiments are carried out to test the technique against a mainstream and an alternative microarray analysis method. Our process is shown to reduce variability in the final expression results.
关 键 词: 微阵列技术; 背景去除工艺技术; 区域局部背景
课程来源: 视频讲座网
最后编审: 2020-06-06:张荧(课程编辑志愿者)
阅读次数: 34