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A study of performance of Longest Common Subsequence identification with sequence identity of biosequences

机译:具有生物序列序列同一性的最长共同子序列鉴定的性能研究

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摘要

Searching for clue to the result with biosequences is an important area of research for computational scientists in bioinformatics. The sequences are longer and demand more and more computational power in order that the result yields benefits to the society. More often the computational results are used in obtaining quick clue to the expected results of lengthy laboratory process. The identity and similarity between sequences provide the basic clue and guidance as to how to progress with work. This paper analyses SRLCS algorithm with the tools like CLUSTAL-W, and MUSCLE in identifying Longest Common Subsequence (LCS) with reference to identity between the bio sequences.
机译:利用生物序列寻找结果的线索是生物信息学计算科学家的重要研究领域。序列更长,需要越来越多的计算能力,以使结果对社会有利。通常,计算结果可用于快速了解冗长的实验室过程的预期结果。序列之间的同一性和相似性为如何进行工作提供了基本的线索和指导。本文使用CLUSTAL-W和MUSCLE等工具分析SRLCS算法,以参考生物序列之间的同一性来识别最长公共子序列(LCS)。

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