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Updated: Jun 25, 2026
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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
Published on: May 31, 2011
ModuleDigger: an itemset mining framework for the detection of cis-regulatory modules
Hong Sun1, Tijl De Bie, Valerie Storms
1Department of Electrical Engineering, Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Leuven, Belgium. hong.sun@esat.kuleuven.be
BMC Bioinformatics
|February 12, 2009
Summary
This study introduces an efficient itemset mining strategy for detecting cis-regulatory modules (CRMs) in large gene sets. The method successfully prioritizes biologically relevant CRMs using numerous transcription factor binding sites.
Area of Science:
- Genomics
- Computational Biology
- Bioinformatics
Background:
- Detecting cis-regulatory modules (CRMs) is crucial for understanding eukaryotic transcriptional regulation.
- Current in silico methods for CRM detection are computationally intensive, limiting their application to small datasets and few transcription factors (TFs).
Purpose of the Study:
- To develop a computationally efficient strategy for detecting cis-regulatory modules (CRMs).
- To enable the analysis of large gene sets and a wide range of transcription factor binding sites (TFBS).
Main Methods:
- An itemset mining based strategy was developed for computational CRM detection.
- The method was tested on a large benchmark dataset derived from ChIP-Chip analysis.
- Performance was compared against established CRM detection tools.
Main Results:
- The itemset mining approach demonstrated computational efficiency.
- The strategy successfully prioritized biologically valid CRMs from large sets of coregulated genes.
- The method effectively utilized binding sites for numerous potential TFs.
Conclusions:
- The combination of itemset mining and a statistical scoring scheme offers an efficient way to detect CRMs.
- This approach overcomes limitations of existing methods, enabling analysis of larger and more complex biological datasets.
- The developed strategy enhances the discovery of regulatory elements driving gene expression.
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