Point pattern matching in the analysis of two-dimensional gel electropherograms.

In the automation of proteome analysis, matching of two-dimensional (2-D) electropherograms represents a bottleneck in the process. Here we present a point pattern recognition approach to the matching of spots in 2-D electropherograms. The algorithm is based on a comparison of spot neighborhoods, converted to point patterns between reference and compared gels. The neighborhood was characterized by a syntactic descriptor which minimized the influence of spot displacements. A combined criterion utilizing the similarity of point patterns and a metric definition of position similarity was derived. The efficiency and accuracy of the algorithm was tested on a set of 69 gels with different levels of similarity. For a typical gel the accuracy of matching was higher than 98% and the number of correctly identified spots was higher than 95%.