Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology
Proceedings of the Fourth International Conference on Intelligent Systems for Molecular Biology
Computing Largest Common Point Sets under Approximate Congruence
ESA '00 Proceedings of the 8th Annual European Symposium on Algorithms
Algorithmic Aspects of Protein Structure Similarity
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
An O(v|v| c |E|) algoithm for finding maximum matching in general graphs
SFCS '80 Proceedings of the 21st Annual Symposium on Foundations of Computer Science
Finding Largest Well-Predicted Subset of Protein Structure Models
CPM '08 Proceedings of the 19th annual symposium on Combinatorial Pattern Matching
Algorithms for optimal protein structure alignment
Bioinformatics
Optimizing a Widely Used Protein Structure Alignment Measure in Expected Polynomial Time
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Improved Algorithms for Matching r-Separated Sets with Applications to Protein Structure Alignment
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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We study the well-known Largest Common Point-set (LCP) under Bottleneck Distance Problem. Given two proteins a and b (as sequences of points in three-dimensional space) and a distance cutoff \sigma, the goal is to find a spatial superposition and an alignment that maximizes the number of pairs of points from a and b that can be fit under the distance \sigma from each other. The best to date algorithms for approximate and exact solution to this problem run in time O(n^8 ) and O(n^{32} ), respectively, where n represents protein length. This work improves runtime of the approximation algorithm and the expected runtime of the algorithm for absolute optimum for both order-dependent and order-independent alignments. More specifically, our algorithms for near-optimal and optimal sequential alignments run in time O(n^7 \log n) and O(n^{14} \log n), respectively. For nonsequential alignments, corresponding running times are O(n^{7.5} ) and O(n^{14.5} ).