M-tree: An Efficient Access Method for Similarity Search in Metric Spaces
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
A Probabilistic Spell for the Curse of Dimensionality
ALENEX '01 Revised Papers from the Third International Workshop on Algorithm Engineering and Experimentation
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Similarity Search: The Metric Space Approach (Advances in Database Systems)
Unified framework for fast exact and approximate search in dissimilarity spaces
ACM Transactions on Database Systems (TODS)
On optimizing the non-metric similarity search in tandem mass spectra by clustering
ISBRA'12 Proceedings of the 8th international conference on Bioinformatics Research and Applications
Algorithmic exploration of axiom spaces for efficient similarity search at large scale
SISAP'12 Proceedings of the 5th international conference on Similarity Search and Applications
SimTandem: similarity search in tandem mass spectra
SISAP'12 Proceedings of the 5th international conference on Similarity Search and Applications
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In biological applications, the tandem mass spectrometry is a widely used method for determining protein and peptide sequences from an ''in vitro'' sample. The sequences are not determined directly, but they must be interpreted from the mass spectra, which is the output of the mass spectrometer. This work is focused on a similarity-search approach to mass spectra interpretation, where the parameterized Hausdorff distance (d"H"P) is used as the similarity. In order to provide an efficient similarity search under d"H"P, the metric access methods and the TriGen algorithm (controlling the metricity of d"H"P) are employed. Moreover, the search model based on the d"H"P supports posttranslational modifications (PTMs) in the query mass spectra, what is typically a problem when an indexing approach is used. Our approach can be utilized as a coarse filter by any other database approach for mass spectra interpretation.