Computer Science ›› 2018, Vol. 45 ›› Issue (4): 252-256.doi: 10.11896/j.issn.1002-137X.2018.04.042

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Distinguishing Sequence Patterns Mining Based on Density and Gap Constraints

WEI Qin-shuang, WU You-xi, LIU Jing-yu and ZHU Huai-zhong   

  • Online:2018-04-15 Published:2018-05-11

Abstract: Distinguishing patterns mining is an important branch of sequence patterns mining,and distinguishing patterns with density constraint can help biologists to find the distribution of special factors on biological sequences.This paper proposed an algorithm,named MPDG(Mining distinguishing sequence Patterns based on Density and Gap constraint),which employs Nettree data structure to mine the distinguishing patterns satisfying the density and gap constraints.The algorithm is efficient since it calculates all super-patterns’ supports of current pattern with one-way scanning the sequence database.Experimental results on real protein datasets verify the effectiveness of MPDG.

Key words: Pattern mining,Distinguishing pattern,Density constraint,Nettree

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