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An Algorithmic Framework for Motif Discovery Problems in Weighted Sequences

机译:加权序列中主题发现问题的算法框架

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摘要

A weighted sequence is a string in which a set of characters may appear at each position with respective probabilities of occurrence. A common task is to locate a given motif in a weighted sequence in exact, approximate or bounded gap form, with presence probability not less than a given threshold. The motif could be a normal non-weighted string or even a string with don't care symbols. We give an algorithmic framework that is capable of tackling above motif discovery problems. Utilizing the notion of maximal factors, the framework provides an approach for reducing each problem to equivalent problem in non-weighted strings without any time degradation.
机译:加权序列是一个字符串,其中一组字符可能以各自的出现概率出现在每个位置。常见的任务是以精确,近似或有界的缺口形式按加权顺序定位给定的基序,其存在概率不小于给定的阈值。主题可以是普通的非加权字符串,甚至可以是带有无关符号的字符串。我们提供了一种能够解决上述主题发现问题的算法框架。利用最大因子的概念,该框架提供了一种方法,可以将每个问题简化为非加权字符串中的等价问题,而不会造成任何时间损失。

著录项

  • 来源
    《Algorithms and complexity》|2010年|p.335-346|共12页
  • 会议地点 Rome(IT);Rome(IT)
  • 作者单位

    College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, Zhejiang 310023, China;

    Department of Computer Science and Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China;

    Department of Computer Science, King's College London Strand, London WC2R 2LS, England;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算技术、计算机技术;
  • 关键词

  • 入库时间 2022-08-26 13:58:08

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