發(fā)布時(shí)間：2018-06-19 21:30

  本文選題：近似匹配 + 通配符��； 參考：《模式識別與人工智能》2016年10期

【摘要】：從生物序列中發(fā)現(xiàn)有意義的頻繁模式已經(jīng)成為生物信息領(lǐng)域研究的重要任務(wù).文中提出基于打分矩陣的生物序列頻繁模式挖掘算法.首先構(gòu)造近似匹配得分矩陣,用于處理帶通配符間隔約束的模式匹配問題中插入、替換、刪除操作.然后設(shè)計(jì)基于打分矩陣的近似模匹配方法獲取模式在序列中的近似出現(xiàn)次數(shù).最后采用數(shù)據(jù)驅(qū)動(dòng)模式生成方法和Apriori-like剪枝策略避免產(chǎn)生過多不必要的候選模式.在蛋白質(zhì)和DNA序列上的實(shí)驗(yàn)表明文中算法性能更優(yōu),可用于挖掘不同序列的共同頻繁模式.
[Abstract]:The discovery of meaningful frequent patterns from biological sequences has become an important task in the field of biological information. An algorithm for frequent pattern mining of biological sequences based on scoring matrix is proposed in this paper. First, the approximate matching score matrix is constructed to deal with the insertion, replacement and deletion operations in pattern matching problems with wildcard spacing constraints. Then the approximate mode matching method based on the scoring matrix is designed to obtain the approximate occurrence times of the pattern in the sequence. Finally, data-driven pattern generation and Apriori-like pruning strategy are used to avoid unnecessary candidate patterns. Experiments on protein and DNA sequences show that the proposed algorithm has better performance and can be used to mine common frequent patterns of different sequences.
【作者單位】： 合肥工業(yè)大學(xué)計(jì)算機(jī)與信息學(xué)院;Department
【基金】：國家自然科學(xué)基金-海外及港澳學(xué)者合作研究基金項(xiàng)目(No.61229301) 國家自然科學(xué)基金青年基金項(xiàng)目(No.61305062)資助~~
【分類號】：TP311.13
，

本文編號：2041354