New algorithmic approaches to protein spot detection and pattern matching in two‐dimensional electrophoresis gel databases

Protein spot identification in two‐dimensional electrophoresis gels can be supported by the comparison of gel images accessible in different World Wide Web two‐dimensional electrophoresis (2‐DE) gel protein databases. The comparison may be performed either by visual cross‐matching between gel images or by automatic recognition of similar protein spot patterns. A prerequisite for the automatic point pattern matching approach is the detection of protein spots yielding the x(s),y(s) coordinates and integrated spot intensities i(s). For this purpose an algorithm is developed based on a combination of hierarchical watershed transformation and feature extraction methods. This approach reduces the strong over‐segmentation of spot regions normally produced by watershed transformation. Measures for the ellipticity and curvature are determined as features of spot regions. The resulting spot lists containing x(s),y(s),i(s)‐triplets are calculated for a source as well as for a target gel image accessible in 2‐DE gel protein databases. After spot detection a matching procedure is applied. Both the matching of a local pattern vs. a full 2‐DE gel image and the global matching between full images are discussed. Preset slope and length tolerances of pattern edges serve as matching criteria. The local matching algorithm relies on a data structure derived from the incremental Delaunay triangulation of a point set and a two‐step hashing technique. For the incremental construction of triangles the spot intensities are considered in decreasing order. The algorithm needs neither landmarks nor an a priori image alignment. A graphical user interface for spot detection and gel matching is written in the Java programming language for the Internet. The software package called CAROL (http://gelmatching.inf.fu‐berlin.de) is realized in a client‐server architecture.