Two-Phase Quantum Based Evolutionary Algorithm for Multiple Sequence Alignment

Authors:
Hongwei Huo;Vojislav Stojkovic
Affiliations:
School of Computer Science and Technology, Xidian University, Xi'an 710071, China;Computer Science Department, Morgan State University, CA205, 1700 East Cold Spring Lane, Baltimore, MD 21251, USA
Venue:
Computational Intelligence and Security
Year:
2007

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Abstract

The paper presents a two-phase quantum based evolution algorithm for multiple sequence alignment problem,called TPQEAlign. TPQEAlign uses a new probabilistic representation, qubit, that can represent a linear superposition of individuals of solutions. Combined with strategy for the optimization of initial search space, TPQEAilgn is proposed as follows. It consists of two phases. In the first phase, a promising initial value is searched and stored. Each local group has a different value of qubit from other local groups to explore a different search space each. In the second phase, we initialize the population using the stored resulting obtained in the first phase. The effectiveness and performance of TPQEAlign are demonstrated by testing cases in BAliBASE. Comparisons were made with the experimental results of QEAlign and several popular programs, such as CLUSTALX and SAGA. The experiments show that TPQEAlign is efficient and competent with CLUSTALX and SAGA.