Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Multiple biomolecular sequence alignment is among the most important and challenging tasks in computational biology. It is characterized by great complexity in processing time. , a multiple-sequence alignment system is reported which combines the techniques of genetic algorithms and pairwise dynamic programming. Genetic algorithms are stochastic approaches for efficient and robust search. By converting biomolecular sequence alignment into a problem of searching for an optimal or a near-optimal point in a solution space, a genetic algorithm is used to find match blocks very efficiently. A pairwise dynamic programming is then applied to the subsequences beten the match blocks. Combining the strengths of the two methods, the system achieves high efficiency and high alignment quality. , the system is described in detail. The system's performance is analyzed and the experimental results are presented.
['Ching Zhang', 'Andrew K. C. Wong']
I am writing a research paper on a idea Toward efficient multiple molecular sequence alignment: a system of genetic algorithm and dynamic programming
[{"from": "human", "value": "I am writing a research paper on a idea Toward efficient multiple molecular sequence alignment: a system of genetic algorithm and dynamic programming"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Multiple biomolecular sequence alignment is among the most important and challenging tasks in computational biology. It is characterized by great complexity in processing time. , a multiple-sequence alignment system is reported which combines the techniques of genetic algorithms and pairwise dynamic programming. Genetic algorithms are stochastic approaches for efficient and robust search. By converting biomolecular sequence alignment into a problem of searching for an optimal or a near-optimal point in a solution space, a genetic algorithm is used to find match blocks very efficiently. A pairwise dynamic programming is then applied to the subsequences beten the match blocks. Combining the strengths of the two methods, the system achieves high efficiency and high alignment quality. , the system is described in detail. The system's performance is analyzed and the experimental results are presented."}]