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An image analysis suite for spot detection and spot matching in two-dimensional electrophoresis gels

机译:用于二维电泳凝胶中斑点检测和斑点匹配的图像分析套件

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摘要

We propose a suite of novel algorithms for image analysis of protein expression images obtained from 2-D electrophoresis. These algorithms are a segmentation algorithm for protein spot identification, and an algorithm for matching protein spots from two corresponding images for differential expression study. The proposed segmentation algorithm employs the watershed transformation, k-means analysis, and distance transform to locate the centroids and to extract the regions of the proteins spots. The proposed spot matching algorithm is an integration of the hierarchical-based and optimization-based methods. The hierarchical method is first used to find corresponding pairs of protein spots satisfying the local cross-correlation and overlapping constraints. The matching energy function based on local structure similarity, image similarity, and spatial constraints is then formulated and optimized. Our new algorithm suite has been extensively tested on synthetic and actual 2-D gel images from various biological experiments, and in quantitative comparisons with ImageMaster2D Platinum (TM) the proposed algorithms exhibit better spot detection and spot matching.
机译:我们提出了一套新颖的算法,用于从二维电泳获得的蛋白质表达图像的图像分析。这些算法是用于蛋白质斑点识别的分割算法,以及用于匹配来自两个对应图像的蛋白质斑点以进行差异表达研究的算法。提出的分割算法利用分水岭变换,k-均值分析和距离变换来定位质心并提取蛋白质斑点的区域。所提出的点匹配算法是基于分层和基于优化的方法的集成。首先使用分层方法来找到满足局部互相关和重叠约束的相应的蛋白质斑点对。然后制定和优化基于局部结构相似性,图像相似性和空间约束的匹配能量函数。我们的新算法套件已经在来自各种生物学实验的合成和实际二维凝胶图像上进行了广泛的测试,并且与ImageMaster2D Platinum(TM)进行定量比较,提出的算法显示出更好的斑点检测和斑点匹配。

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