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ModuleMaster: a new tool to decipher transcriptional regulatory networks
Clemens Wrzodek1, Adrian Schröder, Andreas Dräger
1Center for Bioinformatics Tübingen (ZBIT), University of Tübingen, Sand 1, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de
Bio Systems
|October 13, 2009
Summary
ModuleMaster is a new tool that identifies cis-regulatory modules (CRMs) in gene expression data. It improves CRM detection by analyzing transcription factor binding and gene relationships for better biological insights.
Area of Science:
- Bioinformatics
- Computational Biology
- Systems Biology
Background:
- Identifying cis-regulatory modules (CRMs) is crucial for understanding gene regulation.
- Existing methods may not fully capture complex regulatory relationships.
Purpose of the Study:
- To present ModuleMaster, a novel application for detecting cis-regulatory modules (CRMs).
- To introduce an improved method for CRM detection that integrates transcription factor binding and multivariate functional relationships.
Main Methods:
- The ModuleMaster application integrates data from microarray and clustering experiments.
- It employs a newly developed method considering transcription factor binding and functional relationships.
- The software offers a graphical user interface and command-line options for batch processing.
Main Results:
- ModuleMaster successfully identifies cis-regulatory modules (CRMs) in co-expressed gene sets.
- The application facilitates visualization of detected CRMs and regulatory networks.
- Generated outputs include GraphML, R-based visualizations, and SBML files for modeling.
Conclusions:
- ModuleMaster provides a comprehensive workbench for CRM detection and analysis.
- Its advanced method enhances the accuracy of CRM identification.
- The software supports large-scale analysis and subsequent modeling of regulatory networks.
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Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome. Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...
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