The Research Of Sequence Alignment In Bioinformatics

Sequence alignment is a basic information processing method of bioinformation. It's very important in founding the Nucleic acid and protein sequences on the function, structure and evolution information. With the surging of the data in the biological sequence database, The Development of both high sensitivity and high efficiency of biological Algorithm is extremely urgent. Immune genetic algorithm considered genetic algorithm together with the immune theory in the framework of the traditional genetic algorithm. It introduced many features of the immune system, such as the immune regulatory mechanism and the Diversity preservation strategy Etc. It is effective in the prevention of premature convergence in the search process and other issues, and it is a more effective optimization.The development and research content of bioinformatics and the problems of related sequence alignment algorithms is firstly described, and then it describes the impact of sequence alignment in space penalty strategy, similarity scoring matrix and the objective function on the results in details. According to the number of sequences .It introduces the correlation algorithms of pair-wise sequence alignment and multiple sequence alignment, systematically introduces the dot-plot algorithm, dynamic programming algorithm which are the pair-wise alignment algorithm ,and the progressive multiple sequence alignment algorithm ,iterative multiple sequence alignment algorithms which based on iterative strategy, it also presents the relevant classical algorithms, such as CLUSTALW based on progressive algorithm and iterative improvement of the genetic algorithm for multiple sequence alignment SAGA.After, the article describes the genetic algorithm and the principle of immune genetic algorithm proposed and designs a immune genetic algorithm for multiple sequence alignment based on antigen recognition, antibody diversity preservation strategy and the characteristics of immune memory in immune system, the biological immune systems is introduced into the genetic algorithm for multiple sequence alignment, through the calculation of the affinity between antibodies and immune-based distance vector selection method to promote and inhibit the antibody, while retaining all of the optimum antibody ensures the diversity of antibodies, Thus avoiding the problem of premature convergence when using genetic algorithms for sequence alignment ,obtain the global optimal solution, As the same time, comparing with information entropy based immune genetic algorithms the Vector-based immune genetic algorithms has reduced the a priori input parameters and improves the convergence speed. Finally, the paper tests the feasibility of the algorithm and achieved good results.