A probabilistic coding based quantum genetic algorithm for multiple sequence alignment.
نویسندگان
چکیده
This paper presents an original Quantum Genetic algorithm for Multiple sequence ALIGNment (QGMALIGN) that combines a genetic algorithm and a quantum algorithm. A quantum probabilistic coding is designed for representing the multiple sequence alignment. A quantum rotation gate as a mutation operator is used to guide the quantum state evolution. Six genetic operators are designed on the coding basis to improve the solution during the evolutionary process. The features of implicit parallelism and state superposition in quantum mechanics and the global search capability of the genetic algorithm are exploited to get efficient computation. A set of well known test cases from BAliBASE2.0 is used as reference to evaluate the efficiency of the QGMALIGN optimization. The QGMALIGN results have been compared with the most popular methods (CLUSTALX, SAGA, DIALIGN, SB_PIMA, and QGMALIGN) results. The QGMALIGN results show that QGMALIGN performs well on the presenting biological data. The addition of genetic operators to the quantum algorithm lowers the cost of overall running time.
منابع مشابه
An Application of the ABS LX Algorithm to Multiple Sequence Alignment
We present an application of ABS algorithms for multiple sequence alignment (MSA). The Markov decision process (MDP) based model leads to a linear programming problem (LPP), whose solution is linked to a suggested alignment. The important features of our work include the facility of alignment of multiple sequences simultaneously and no limit for the length of the sequences. Our goal here is to ...
متن کاملPSAR: measuring multiple sequence alignment reliability by probabilistic sampling
Multiple sequence alignment, which is of fundamental importance for comparative genomics, is a difficult problem and error-prone. Therefore, it is essential to measure the reliability of the alignments and incorporate it into downstream analyses. We propose a new probabilistic sampling-based alignment reliability (PSAR) score. Instead of relying on heuristic assumptions, such as the correlation...
متن کاملgpALIGNER: A Fast Algorithm for Global Pairwise Alignment of DNA Sequences
Bioinformatics, through the sequencing of the full genomes for many species, is increasingly relying on efficient global alignment tools exhibiting both high sensitivity and specificity. Many computational algorithms have been applied for solving the sequence alignment problem. Dynamic programming, statistical methods, approximation and heuristic algorithms are the most common methods appli...
متن کاملProbabilistic Modeling and Alignment of Protein Structure Families
ABSTRACT Motivation: Multiple protein structure alignment is an important tool in bioinformatics. Although several algorithms exist for this purpose, recent publications highlight inconsistencies among alignments from different algorithms and, increasingly, the recognition that alignments by a single algorithm may be highly unstable under small fluctuations of the input protein structures arisi...
متن کاملDesigning a quantum genetic controller for tracking the path of quantum systems
Based on learning control methods and computational intelligence, control of quantum systems is an attractive field of study in control engineering. What is important is to establish control approach ensuring that the control process converges to achieve a given control objective and at the same time it is simple and clear. In this paper, a learning control method based on genetic quantum contr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Computational systems bioinformatics. Computational Systems Bioinformatics Conference
دوره 7 شماره
صفحات -
تاریخ انتشار 2008