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THE COMPARISON OF THREE METHODS FOR CHROMOSOMAL ABNORMALITY DETECTION

机译:三种染色体异常检测方法的比较

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摘要

The connection between certain human diseases and abnormal changes in chromosomes was discovered nearly 50 years ago. However, the detection of these abnormalities turned out to be a difficult task because both microscopic technologies and biochemical diagnostic techniques have their limitations. In the beginning of the century, a method for multiple comparative genome hybridization (array CGH) was introduced and is now been widely used in clinical practice for biochemical diagnostics. The application of array CGH greatly reduces the statistical errors, but not the noise in the results. As such, the time and material expenses necessary for reliable localization of abnormal parts of chromosomes by the means of biochemical techniques, is not significantly reduced. Algorithms for localization of contrast parts in noisy sequences can improve the situation. We implemented and tested two algorithms for this purpose. The first is the "edge detector" algorithm introduced by J. Canny. The second one is the DotHelix algorithm developed by A. M. Leontovich, L. I. Brodsky, and A. E. Gorbalenya. In this paper we compare the two implementations against biochemical method in processing data produced by array CGH.
机译:大约50年前发现了某些人类疾病与染色体异常变化之间的联系。但是,由于显微镜技术和生化诊断技术都具有局限性,因此检测这些异常是一项艰巨的任务。在本世纪初,引入了多种比较基因组杂交的方法(阵列CGH),目前已广泛用于生化诊断的临床实践中。阵列CGH的应用极大地减少了统计误差,但没有减少结果中的噪声。这样,通过生物化学技术可靠地定位染色体的异常部分所需的时间和材料费用没有显着减少。用于在噪声序列中定位对比部分的算法可以改善这种情况。为此,我们实现并测试了两种算法。第一种是J. Canny提出的“边缘检测器”算法。第二个是A. M. Leontovich,L。I. Brodsky和A. E. Gorbalenya开发的DotHelix算法。在本文中,我们在处理阵列CGH产生的数据时,将两种实现与生化方法进行了比较。

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