A Novel Gaussian Extrapolation Approach for 2-D Gel Electrophoresis Saturated Protein Spots

Analysis of images obtained from two-dimensional gel electrophoresis (2-D GE) is a topic of utmost importance in bioinformatics research, since commercial and academic software currently available have proven to be neither completely effective nor fully automatic, often requiring manual revision and refinement of computer generated matches. In this chapter, 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 proteins quantification, providing more reliable image analysis results. The method is validated for processing highly exposed 2-D GE images, comparing reconstructed spots with the corresponding non-saturated image. The results demonstrate that the algorithm enables correct spot quantification.