Maximal pattern matching with flexible wildcard gaps and one-off constraint

Pattern matching is a fundamental operation in finding knowledge from large amount of biosequence data. Finding patterns help in analyzing the property of a sequence. This paper focuses on the problem of maximal pattern matching with flexible wildcard gaps and length constraints under the one-off condition. The problem is to find the maximum number of occurrences of a pattern P with user specified wildcard gap between every two consecutive letters of P in a biological sequence S under the one-off condition and constraint on the overall length of the matching occurrence. To obtain the optimal solution for this problem is difficult. We propose a heuristic algorithm, MOGO, based on the Nettree data structure to solve this problem. Theoretical analysis and experimental results demonstrate that MOGO performs better than the existing algorithms in most of the cases when tested on real world biological sequences.