Evolving DNA motifs to predict GeneChip probe performance

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 in...

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Detalles Bibliográficos
Autores principales: Langdon, WB, Harrison, AP
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2679018/
https://www.ncbi.nlm.nih.gov/pubmed/19298675
http://dx.doi.org/10.1186/1748-7188-4-6
Descripción
Sumario: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.

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