Discovering consensus patterns in biological databases

Mohamed Y. ElTabakh*, Walid G. Aref, Mourad Ouzzani, Mohamed H. Ali

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Consensus patterns, like motifs and tandem repeats, are highly conserved patterns with very few substitutions where no gaps are allowed. In this paper, we present a progressive hierarchical clustering technique for discovering consensus patterns in biological databases over a certain length range. This technique can discover consensus patterns with various requirements by applying a post-processing phase. The progressive nature of the hierarchical clustering algorithm makes it scalable and efficient. Experiments to discover motifs and tandem repeats on real biological databases show significant performance gain over non-progressive clustering techniques.

Original languageEnglish
Title of host publicationData Mining and Bioinformatics - First International Workshop, VDMB 2006, Revised Selected Papers
PublisherSpringer Verlag
Pages170-184
Number of pages15
ISBN (Print)3540689702, 9783540689706
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event1st International Workshop on Data Mining and Bioinformatics, VDMB 2006 - Seoul, Korea, Republic of
Duration: 11 Sept 200611 Sept 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4316 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Workshop on Data Mining and Bioinformatics, VDMB 2006
Country/TerritoryKorea, Republic of
CitySeoul
Period11/09/0611/09/06

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