@inproceedings{718153b3ba0a496fa3469eff5d0b76c7,
title = "Discovering consensus patterns in biological databases",
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.",
author = "ElTabakh, {Mohamed Y.} and Aref, {Walid G.} and Mourad Ouzzani and Ali, {Mohamed H.}",
year = "2006",
doi = "10.1007/11960669_15",
language = "English",
isbn = "3540689702",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "170--184",
booktitle = "Data Mining and Bioinformatics - First International Workshop, VDMB 2006, Revised Selected Papers",
address = "Germany",
note = "1st International Workshop on Data Mining and Bioinformatics, VDMB 2006 ; Conference date: 11-09-2006 Through 11-09-2006",
}