Labeled point pattern matching by Delaunay triangulation and maximal cliques
Pattern Recognition
Introduction to algorithms
An application of point pattern matching in astronautics
Journal of Symbolic Computation - Special issue on “algorithms: implementation, libraries and use”
Davenport-Schinzel sequences and their geometric applications
Davenport-Schinzel sequences and their geometric applications
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Combinatorial and experimental results for randomized point matching algorithms
Selected papers from the 12th annual symposium on Computational Geometry
An applied point pattern matching problem: comparing 2D patterns of protein spots
Discrete Applied Mathematics - Special issue on the 13th European workshop on computational geometry CG '97
Approximation algorithms for projective clustering
SODA '00 Proceedings of the eleventh annual ACM-SIAM symposium on Discrete algorithms
Taking a Walk in a Planar Arrangement
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
A landmark extraction method for protein 2DE gel images based on multi-dimensional clustering
Artificial Intelligence in Medicine
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In proteomics 2-dimensional gel electrophoresis (2-DE) is a separation technique for proteins. The resulting protein spots can be identified by either using picking robots and subsequent mass spectrometry or by visual cross inspection of a new gel image with an already analyzed master gel. Difficulties especially arise from inherent noise and irregular geometric distortions in 2-DE images. Aiming at the automated analysis of large series of 2-DE images, or at the even more difficult interlaboratory gel comparisons, the bottleneck is to solve the two most basic algorithmic problems with high quality: Identifying protein spots and computing a matching between two images. For the development of the analysis software CAROL at Freie Universität Berlin we have reconsidered these two problems and obtained new solutions which rely on methods from computational geometry. Their novelties are: 1. Spot detection is also possible for complex regions formed by several “merged” (usually saturated) spots; 2. User-defined landmarks are not necessary for the matching. Furthermore, images for comparison are allowed to represent different parts of the entire protein pattern, which only partially “overlap”. The implementation is done in a client server architecture to allow queries via the Internet. We also discuss and point at related theoretical questions in computational geometry.