Department of Control and Computer Engineering, Politecnico di Torino, Torino 10129, Italy.
Genomics Proteomics Bioinformatics. 2012 Dec;10(6):336-44. doi: 10.1016/j.gpb.2012.06.005. Epub 2012 Nov 7.
Analysis of images obtained from two-dimensional gel electrophoresis (2D-GE) is a topic of utmost importance in bioinformatics research, since commercial and academic software available currently has proven to be neither completely effective nor fully automatic, often requiring manual revision and refinement of computer generated matches. In this work, we present an effective technique for the detection and the reconstruction of over-saturated protein spots. Firstly, the algorithm reveals overexposed areas, where spots may be truncated, and plateau regions caused by smeared and overlapping spots. Next, it reconstructs the correct distribution of pixel values in these overexposed areas and plateau regions, using a two-dimensional least-squares fitting based on a generalized Gaussian distribution. Pixel correction in saturated and smeared spots allows more accurate quantification, providing more reliable image analysis results. The method is validated for processing highly exposed 2D-GE images, comparing reconstructed spots with the corresponding non-saturated image, demonstrating that the algorithm enables correct spot quantification.
二维凝胶电泳（2D-GE）图像分析是生物信息学研究中至关重要的课题，因为目前可用的商业和学术软件既不完全有效，也不完全自动，通常需要手动修正和完善计算机生成的匹配。在这项工作中，我们提出了一种有效的检测和重建过饱和蛋白斑点的技术。首先，该算法揭示了过度曝光的区域，在这些区域中，斑点可能会被截断，以及由于斑点模糊和重叠而产生的平坦区域。接下来，它使用基于广义高斯分布的二维最小二乘拟合来重建这些过曝光区域和平坦区域中正确的像素值分布。对过饱和和模糊斑点的像素校正可以实现更准确的定量，提供更可靠的图像分析结果。该方法通过处理高度曝光的 2D-GE 图像进行了验证，将重建的斑点与相应的非饱和图像进行了比较，证明了该算法能够实现正确的斑点定量。
