Automatic techniques for gridding CDNA microarray images

N. Kaabouch, H. Shahbazkia
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引用次数: 4

Abstract

Microarray is considered an important instrument and powerful new technology for large-scale gene sequence and gene expression analysis. One of the major challenges of this technique is the image processing phase. The accuracy of this phase has an important impact on the accuracy and effectiveness of the subsequent gene expression and identification analysis. The processing can be organized mainly into four steps: gridding, spot isolation, segmentation, and quantification. Although several commercial software packages are now available, microarray image analysis still requires some intervention by the user, and thus a certain level of image processing expertise. This paper describes and compares four techniques that perform automatic gridding and spot isolation. The proposed techniques are based on template matching technique, standard deviation, sum, and derivative of these profiles. Experimental results show that the accuracy of the derivative of the sum profile is highly accurate compared to other techniques for good and poor quality microarray images.
CDNA微阵列图像的自动网格化技术
微阵列被认为是大规模基因测序和基因表达分析的重要工具和强有力的新技术。该技术的主要挑战之一是图像处理阶段。这一阶段的准确性对后续基因表达和鉴定分析的准确性和有效性具有重要影响。处理过程主要分为四个步骤:网格化、斑点隔离、分割和量化。虽然现在有几个商业软件包可用,但微阵列图像分析仍然需要用户的一些干预,因此需要一定程度的图像处理专业知识。本文描述并比较了四种实现自动网格和斑点隔离的技术。所提出的技术是基于模板匹配技术、标准偏差、和和这些轮廓的导数。实验结果表明,对于高质量和低质量的微阵列图像,与其他技术相比,求和轮廓导数的精度很高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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