Computational geometry: an introduction
Computational geometry: an introduction
Two algorithms for nearest-neighbor search in high dimensions
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Nearest neighbor queries in metric spaces
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Handbook of discrete and computational geometry
Multidimensional binary search trees used for associative searching
Communications of the ACM
Using motion planning to study protein folding pathways
RECOMB '01 Proceedings of the fifth annual international conference on Computational biology
Proceedings of the sixth annual international conference on Computational biology
Wavelets for Computer Graphics: A Primer, Part 1
IEEE Computer Graphics and Applications
High-dimensional computational geometry
High-dimensional computational geometry
Alternate Representation of Distance Matrices for Characterization of Protein Structure
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Fast protein structure alignment algorithm based on local geometric similarity
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Protein structure abstractionand automatic clustering using secondary structure element sequences
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part II
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It is shown that structural similarity between proteins can be decided well with much less information than what is used in common similarity measures. The full Cα representation contains redundant information because of the inherent chain topology of proteins and a limit on their compactness due to excluded volume. A wavelet analysis on random chains and proteins justifies approximating subchains by their centers of mass. For not too compact chain-like structures in general, and proteins in particular, similarity measures that use this approximation are highly correlated to the exact similarity measures and are therefore useful, e.g., as fast filters. Experimental results with such simplified similarity measures in two applications, nearest neighbor search and automatic structural classification show a significant speed up.