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FACC: A Novel Finite Automaton Based on Cloud Computing for the Multiple Longest Common Subsequences Search

机译：FACC：一种基于云计算的新颖的有限自动机，用于多个最长公共子序列搜索

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摘要

Searching for the multiple longest common subsequences (MLCS) has significant applications in the areas of bioinformatics, information processing, and data mining, and so forth, Although a few parallel MLCS algorithms have been proposed, the efficiency and effectiveness of the algorithms are not satisfactory with the increasing complexity and size of biologic data. To overcome the shortcomings of the existing MLCS algorithms, and considering that MapReduce parallel framework of cloud computing being a promising technology for cost-effective high performance parallel computing, a novel finite automaton (FA) based on cloud computing called FACC is proposed under MapReduce parallel framework, so as to exploit a more efficient and effective general parallel MLCS algorithm. FACC adopts the ideas of matched pairs and finite automaton by preprocessing sequences, constructing successor tables, and common subsequences finite automaton to search for MLCS. Simulation experiments on a set of benchmarks from both real DNA and amino acid sequences have been conducted and the results show that the proposed FACC algorithm outperforms the current leading parallel MLCS algorithm FAST-MLCS.
机译：搜索多个最长公共子序列（MLCS）在生物信息学，信息处理和数据挖掘等领域具有重要的应用，尽管已经提出了一些并行MLCS算法，但是该算法的效率和有效性并不令人满意。随着生物数据的复杂性和规模的增加。为了克服现有MLCS算法的缺点，并考虑到云计算的MapReduce并行框架是一种具有成本效益的高性能并行计算的有前途的技术，提出了一种基于云计算的新型有限自动机（FACC），称为FACC。框架，以开发一种更有效的通用并行MLCS算法。 FACC通过对序列进行预处理，构造后继表和公共子序列有限自动机来采用匹配对和有限自动机的思想来搜索MLCS。从真实的DNA和氨基酸序列对一组基准进行了仿真实验，结果表明，所提出的FACC算法优于当前领先的并行MLCS算法FAST-MLCS。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第10期|310328.1-310328.17|共17页
  • 作者

    Yanni Li; Yuping Wang; Liang Bao;

  • 作者单位

    School of Computer Science and Technology, Xidian University, Xi'an 710071, China,School of Software, Xidian University, Xi'an 710071, China;

    School of Computer Science and Technology, Xidian University, Xi'an 710071, China;

    School of Software, Xidian University, Xi'an 710071, China;

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