An efficient seeded tree alignment algorithm for finding the similarity score of two RNA secondary structures

This paper presents an efficient O(n3) time algorithm for solving the seeded tree alignment problem that finds the similarity score of two RNA secondary structures. In the seeded tree alignment problem, a large tree, representing an RNA secondary structure, is converted into a small tree known as seeded tree. After conversion, a comparison operation is being placed to find the similarity score of necessary seed pair of two seeded trees and finally the overall trees. The algorithm is more efficient than the best known algorithm that needs O(n3.5) time.