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Mining the Association Rules of Transcription Factor Binding Sites in Human Tandem Repeats Using Aprior Algorithm | OMICS International | Abstract
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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Research Article

Mining the Association Rules of Transcription Factor Binding Sites in Human Tandem Repeats Using Aprior Algorithm

Zhong-yu Liu and Yi-Yang*

School of Life Sciences, Sichuan University , Chengdu 610064, China

*Corresponding Author:
Yi-Yang
School of Life Sciences
Sichuan University
Chengdu 610064, China
Phone : 85418768,
E-mail : [email protected]

Received date: May 05, 2009; Accepted date: June 12, 2009; Published date: June 13, 2009

Citation: Liu Z, Yang Y (2009) Mining the Association Rules of Transcription Factor Binding Sites in Human Tandem Repeats Using Aprior Algorithm. J Comput Sci Syst Biol 2:180-185. doi:10.4172/jcsb.1000030

Copyright: © 2009 Liu Z, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Tandem repeats (TR) are the most abundant ones in the extragenic region of genomes. Biologists have already found a large number of regulatory elements in this region. These elements may profoundly impact the chromatin structure formation in nucleus and also contain important clues in genetic evolution and phylogenic study. This study attempts to mine rules on how combinations of individual binding sites are distributed tandem repeats in human genome (https://www.trbase2.cn). The association rules mined would facilitate efforts to identify gene classes regulated by similar mechanisms and accurately predict regulatory elements. Herein, the combinations of transcription factor binding sites in the tandem repeats are obtained and, then, data mining techniques are applied to mine the association rules from the combinations of binding sites. In addition, the discovered associations are further pruned to remove those insignificant associations and obtain a set of discovered associations.

Keywords

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