微阵列斑点分割和基因表达分析的新方法

A. Hudaib, H. Fakhouri, Rawan Ghnemat
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引用次数: 2

摘要

DNA微阵列分析是基因组定位的核心。每个微阵列图像包含数以百万计的基因信息。微阵列分析被认为是研究基因组最新和最重要的技术之一。从基因斑点中提取基因信息是芯片分析的关键步骤之一,这些信息代表了基因在芯片中的表达水平。本文提出了一种基于斑点提取片段改进芯片斑点分析的新方法。它不是对微阵列图像的所有斑点区域进行综合分析,而是对每个斑点区域进行独立的分析。本文提供了一个形式模型来增强从基因表达水平得到的强度值在任何强度表达水平的微阵列。本文还介绍了用于微阵列分割的自适应阈值技术。实验结果表明,基因表达强度值的平均值为87.77。关键词:微阵列图像,微阵列分析,图像分割,网格划分,微阵列寻址,斑点定位,斑点提取。
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New methodology for microarray spot segmentation and gene expression analysis
DNA microarray analysis is the main core in genome mapping. Each microarray image contains millions of information about genes. Microarray analysis is considered one of the most recent and important technologies in exploring the genome. One of the key steps in microarray analysis is to extract gene information from the gene spots, these information represent gene expression levels in the microarray. This paper proposes a new methodology to improve microarray spot analysis based on spot extracted segments. It concentrates on each spot segment area independently rather than analyzing all the spots area together of the microarray image. This paper provides a formal model to enhance the intensity values obtained from gene expression levels of the microarray at any intensity expressed level. It also this paper presents the adaptive threshold techniques to be used for microarray segmentation. The experimental results show that the mean of the gene expression intensity value was 87.77.   Key words: Microarray images, microarray analysis, image segmentation, gridding, microarray addressing, spot localization, spot extraction.
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来源期刊
Scientific Research and Essays
Scientific Research and Essays 综合性期刊-综合性期刊
自引率
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发文量
6
审稿时长
3.3 months
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