A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
An energy function and continuous edit process for graph matching
Neural Computation
RECOMB '01 Proceedings of the fifth annual international conference on Computational biology
Structural alignment of large—size proteins via lagrangian relaxation
Proceedings of the sixth annual international conference on Computational biology
Alignment Of Protein Structures With A Memetic Evolutionary Algorithm
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Algorithmic Aspects of Protein Structure Similarity
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Algorithmic aspects of protein folding and protein structure similarity
Algorithmic aspects of protein folding and protein structure similarity
Self Generating Metaheuristics in Bioinformatics: The Proteins Structure Comparison Case
Genetic Programming and Evolvable Machines
Optimal Protein Structure Alignment Using Maximum Cliques
Operations Research
A branch-and-reduce algorithm for the contact map overlap problem
RECOMB'06 Proceedings of the 10th annual international conference on Research in Computational Molecular Biology
The Journal of Machine Learning Research
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Comparison of 3-dimensional protein folds is a core problem in molecular biology. The Contact Map Overlap (CMO) scheme provides one of the most common measures for protein structure similarity. Maximizing CMO is, however, NP-hard. To approximately solve CMO, we combine softassign and dynamic programming. Softassign approximately solves the maximum common subgraph (MCS) problem. Dynamic programming converts the MCS solution to a solution of the CMO problem. We present and discuss experiments using proteins with up to 1500 residues. The results indicate that the proposed method is extremely fast compared to other methods, scales well with increasing problem size, and is useful for comparing similar protein structures.