Simple fast algorithms for the editing distance between trees and related problems
SIAM Journal on Computing
The Tree-to-Tree Correction Problem
Journal of the ACM (JACM)
Multihierarchical Graph Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Matching Problems over 2-Interval Sets
CPM '02 Proceedings of the 13th Annual Symposium on Combinatorial Pattern Matching
Alignment of Trees - An Alternative to Tree Edit
CPM '94 Proceedings of the 5th Annual Symposium on Combinatorial Pattern Matching
Finding Common Subsequences with Arcs and Pseudoknots
CPM '99 Proceedings of the 10th Annual Symposium on Combinatorial Pattern Matching
Local Similarity in RNA Secondary Structures
CSB '03 Proceedings of the IEEE Computer Society Conference on Bioinformatics
A New Distance for High Level RNA Secondary Structure Comparison
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A new constrained edit distance between quotiented ordered trees
Journal of Discrete Algorithms
RNA tree comparisons via unrooted unordered alignments
WABI'12 Proceedings of the 12th international conference on Algorithms in Bioinformatics
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We introduce a new data structure, called MiGaL for “Multiple Graph Layers”, that is composed of various graphs linked together by relations of abstraction/refinement. The new structure is useful for representing information that can be described at different levels of abstraction, each level corresponding to a graph. We then propose an algorithm for comparing two MiGaLs. The algorithm performs a step-by-step comparison starting with the most “abstract” level. The result of the comparison at a given step is communicated to the next step using a special colouring scheme. MiGaLs represent a very natural model for comparing RNA secondary structures that may be seen at different levels of detail, going from the sequence of nucleotides, single or paired with another to participate in a helix, to the network of multiple loops that is believed to represent the most conserved part of RNAs having similar function. We therefore show how to use MiGaLs to very efficiently compare two RNAs of any size at different levels of detail simultaneously.