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Discovering novel cis-regulatory motifs using functional networks
Laurence M Ettwiller1, Johan Rung, Ewan Birney
1European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD, UK.
Genome Research
|May 3, 2003
Summary
This study introduces a novel method for discovering cis-regulatory motifs in yeast (Saccharomyces cerevisiae) by integrating genomic and functional data. The approach successfully identified known and novel motifs, revealing coordinated transcriptional regulation among interacting proteins.
Area of Science:
- Genomics
- Systems Biology
- Bioinformatics
Background:
- Identifying cis-regulatory motifs is crucial for understanding gene regulation.
- Integrating diverse biological data can enhance motif discovery accuracy.
Purpose of the Study:
- To develop and validate a new scoring metric for predicting cis-regulatory motifs in Saccharomyces cerevisiae.
- To explore the relationship between protein interactions and transcriptional coordination.
Main Methods:
- Combined genome information with functional data (protein-protein interactions, metabolic networks).
- Developed a novel scoring metric for motif discovery.
- Utilized brute-force randomization for statistical significance assessment.
Main Results:
- Identified 42 degenerate motifs, covering 40% of yeast genes.
- Five known motifs were rediscovered, along with novel ones.
- Motifs showed spatial positioning, suggesting biological relevance.
- The metric effectively discriminated real motifs from random patterns.
Conclusions:
- The developed metric is a robust tool for cis-regulatory motif discovery.
- Interacting proteins often exhibit coordinated transcriptional regulation, even without apparent co-expression.
- This method has broad applications in biological research.