Evolving DNA motifs to predict GeneChip probe performance

doi:10.1186/1748-7188-4-6

Algorithms for Molecular Biology

Volume 4

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Evolving DNA motifs to predict GeneChip probe performance

WB Langdon¹ and AP Harrison²

¹Department of Computer Science, King's College London, Strand, London, WC2R 2LS, UK

²Biological Sciences, University of Essex, Wivenhoe Park, Colchester, CO4 3SQ, UK

author email corresponding author email

Algorithms for Molecular Biology 2009, 4:6doi:10.1186/1748-7188-4-6


Published:	19 March 2009

Abstract

Background

Affymetrix High Density Oligonuclotide Arrays (HDONA) simultaneously measure expression of thousands of genes using millions of probes. We use correlations between measurements for the same gene across 6685 human tissue samples from NCBI's GEO database to indicated the quality of individual HG-U133A probes. Low correlation indicates a poor probe.

Results

Regular expressions can be automatically created from a Backus-Naur form (BNF) context-free grammar using strongly typed genetic programming.

Conclusion

The automatically produced motif is better at predicting poor DNA sequences than an existing human generated RE, suggesting runs of Cytosine and Guanine and mixtures should all be avoided.