Towards a temporal modeling of the genetic network controlling systemic acquired resistance in Arabidopsis thaliana

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DOIResolve DOI: http://doi.org/10.1109/CIBCB.2010.5510589
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TypeArticle
Proceedings title2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
Conference2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2010), May 2-5, Montréal, Québec
Pages18; # of pages: 8
SubjectInformation and Communications Technologies
AbstractWe studied defense mechanism of the Arabidopsis thaliana subjected to Salicylic Acid (SA) treatment for 0, 1, and 8 hours using a broader application of the frequent itemset approach. Four genotypes of the plant were used in this study, Columbia wild type, mutant npr1, double mutant tga1 ga4 and triple mutant tga2 ga5 ga6. We defined the major patterns of transcription regulation governing pathogen defense mechanism, thereby creating a model of the Systemic Acquired Resistance (SAR) at three time points. The temporal model describes the relationships among the regulators and defines groups of genes that are subject to similar regulation. The results obtained offered a first glimpse into the temporal pattern of the gene network controlling SAR in plant. We found that most of the genes that responded to SA challenge are in fact dependent on one or more of the NPR1 and TGA transcription factors tested in this study.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); NRC Institute for Information Technology; NRC Plant Biotechnology Institute
Peer reviewedYes
NPARC number15261149
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Record identifier0a781464-afcc-445b-8641-add274937326
Record created2010-06-10
Record modified2016-05-09
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