Download | - View accepted manuscript: Towards a temporal modeling of the genetic network controlling systemic acquired resistance in Arabidopsis thaliana (PDF, 727 KiB)
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DOI | Resolve DOI: https://doi.org/10.1109/CIBCB.2010.5510589 |
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Author | Search for: Tchagang, Alain1; Search for: Shearer, Heather2; Search for: Phan, Sieu1; Search for: Famili, Fazel1; Search for: Fobert, Pierre2; Search for: Pan, Youlian1 |
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Affiliation | - National Research Council of Canada. NRC Institute for Information Technology
- National Research Council of Canada. NRC Plant Biotechnology Institute
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Format | Text, Article |
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Conference | 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2010), May 2-5, Montréal, Québec |
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Subject | Information and Communications Technologies |
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Abstract | We 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. |
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Publication date | 2010-05-05 |
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In | |
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Language | English |
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Peer reviewed | Yes |
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NPARC number | 15261149 |
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Export citation | Export as RIS |
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Report a correction | Report a correction (opens in a new tab) |
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Record identifier | 0a781464-afcc-445b-8641-add274937326 |
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Record created | 2010-06-10 |
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Record modified | 2020-04-17 |
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