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A co-evolutionary framework for regulatory motif discovery | IEEE Conference Publication | IEEE Xplore

A co-evolutionary framework for regulatory motif discovery


Abstract:

In previous work, we have shown how an evolutionary algorithm with a clustered population can be used to concurrently discover multiple regulatory motifs present within t...Show More

Abstract:

In previous work, we have shown how an evolutionary algorithm with a clustered population can be used to concurrently discover multiple regulatory motifs present within the promoter sequences of co-expressed genes. In this paper, we extend the algorithm by co-evolving a population of Boolean classification rules in parallel with the motif population. Results using synthetic data suggest that this approach allows poorly conserved motifs to be identified in promoter sequences an order of magnitude longer than using population clustering alone, whilst results using muscle-specific promoter data show the algorithm is able to evolve meaningful sequence classifiers in parallel with motifs-suggesting that co-evolution provides a suitable framework for composite motif discovery within eukaryotic sequences.
Date of Conference: 25-28 September 2007
Date Added to IEEE Xplore: 07 January 2008
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Conference Location: Singapore

References

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