A Fast Biological Data Mining Algorithm Based on Embedded Frequent Subtree

In this paper, we present a fast biological data mining algorithm named IRTM based on embedded frequent subtree. We also advance a string encoding method for representing the trees, a scope-list for extending all substrings and some pruning rules which can further reduce the computational time and space cost. Experimental results show that IRTM algorithm can achieve significantly performance improvement over previous works.