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
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author Langdon, WB
Harrison, AP
author_facet Langdon, WB
Harrison, AP
author_sort Langdon, WB
collection PubMed
description 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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spelling pubmed-26790182009-05-08 Evolving DNA motifs to predict GeneChip probe performance Langdon, WB Harrison, AP Algorithms Mol Biol Research 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. BioMed Central 2009-03-19 /pmc/articles/PMC2679018/ /pubmed/19298675 http://dx.doi.org/10.1186/1748-7188-4-6 Text en Copyright © 2009 Langdon and Harrison; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Langdon, WB
Harrison, AP
Evolving DNA motifs to predict GeneChip probe performance
title Evolving DNA motifs to predict GeneChip probe performance
title_full Evolving DNA motifs to predict GeneChip probe performance
title_fullStr Evolving DNA motifs to predict GeneChip probe performance
title_full_unstemmed Evolving DNA motifs to predict GeneChip probe performance
title_short Evolving DNA motifs to predict GeneChip probe performance
title_sort evolving dna motifs to predict genechip probe performance
topic Research
url 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
work_keys_str_mv AT langdonwb evolvingdnamotifstopredictgenechipprobeperformance
AT harrisonap evolvingdnamotifstopredictgenechipprobeperformance

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