探讨了生物信息挖掘中6模式子序列问题的一个特例,即最长递增子序列(LIS)问题。对于LIS问题,分别用LCS算法、动态规划、动态规划结合二分法进行求解,并分析了这三种算法的时间和空间复杂度,对其中两种算法进行了实现,验证了时间和空间复杂性理论分析的正确性,最后得出了一种高效的LIS算法。
This paper introduced a special problem of 6 pattern subsequence in bioinformatics mining, that was LIS problem. This paper gave three algorithms of the LIS problem, they were LCS-based, dynamic programming, dynamic programming binary search, and analyzed the advantage and disadvantage of the three algorithms, and tested the performance of the three algorithms' complexity through experiment. Finally, it educed an effective LIS algorithm.