Graphic user interface based implementation of longest common subsequence problem in DNA sequencing

Arpan Kumar, Sarbajit Manna
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Abstract

One of the oldest problems in computational biology is biological sequences in which similar portion of two DNA sequence is searched. Global alignment is designed for the same and Longest Common Subsequence (LCS), one of the most basic algorithms in the field of computer science, provides the best solution global alignment irrespective of the shape of its input sequences. The Longest common Subsequence problem with a variable number of strings is variable and strictly more than 2 is known as Multiple Longest Common Subsequence problem (MLCS) and it is an NP-hard problem. Dynamic Programming Algorithm can be employed to solve the same within polynomial time provided the number of strings is known. In this work, using python GUI-library tkinter, the GUI has been built with the code of the LCS problem embedded within the GUI application. This would not only help to see how the strings are being matched inside the program but also the way the optimal solution is produced.
基于图形用户界面的DNA测序中最长公共子序列问题的实现
计算生物学中最古老的问题之一是寻找两个DNA序列的相似部分的生物序列。全局对齐是针对相同的目标而设计的,而LCS算法是计算机科学领域最基本的算法之一,无论其输入序列的形状如何,它都能提供最佳的全局对齐解决方案。可变字符串数的最长公共子序列问题是可变的,且严格大于2,被称为多重最长公共子序列问题(MLCS),它是一个np困难问题。在已知字符串数的情况下,动态规划算法可以在多项式时间内求解。在这项工作中,使用python GUI库tkinter,将LCS问题的代码嵌入到GUI应用程序中构建GUI。这不仅有助于了解字符串在程序中是如何匹配的,而且还有助于了解产生最优解的方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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