Congruence, similarity and symmetries of geometric objects
Discrete & Computational Geometry - ACM Symposium on Computational Geometry, Waterloo
Topologically sweeping an arrangement
Journal of Computer and System Sciences - 18th Annual ACM Symposium on Theory of Computing (STOC), May 28-30, 1986
Pattern Recognition Letters
Computational geometry: algorithms and applications
Computational geometry: algorithms and applications
Topological Sweep in Degenerate Cases
ALENEX '02 Revised Papers from the 4th International Workshop on Algorithm Engineering and Experiments
Algorithms for alignment of mass spectrometry proteomic data
Bioinformatics
Maximum stabbing line in 2D plane
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
EigenMS: de novo analysis of peptide tandem mass spectra by spectral graph partitioning
RECOMB'05 Proceedings of the 9th Annual international conference on Research in Computational Molecular Biology
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Mass spectrometry has become one of the most popular analysis techniques in Proteomics and Systems Biology. With the creation of larger datasets, the automated recalibration of mass spectra becomes important to ensure that every peak in the sample spectrum is correctly assigned to some peptide and protein. Algorithms for recalibrating mass spectra have to be robust with respect to wrongly assigned peaks, as well as efficient due to the amount of mass spectrometry data. The recalibration of mass spectra leads us to the problem of finding an optimal matching between mass spectra under measurement errors.We have developed two deterministic methods that allow robust computation of such a matching: The first approach uses a computational geometry interpretation of the problem, and tries to find two parallel lines with constant distance that stab a maximal number of points in the plane. The second approach is based on finding a maximal common approximate subsequence, and improves existing algorithms by one order of magnitude exploiting the sequential nature of the matching problem. We compare our results to a computational geometry algorithm using a topological line-sweep.