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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Gene Functional Prediction Using Clustering Methods for the Analysis of Tomato Microarray Data
verfasst von : Liliana López-Kleine, José Romeo, Francisco Torres-Avilés
Erschienen in: 7th International Conference on Practical Applications of Computational Biology & Bioinformatics
Verlag: Springer International Publishing
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Molecular mechanisms of plant-pathogen interaction have been studied thoroughly because of its importance for crop production and food supply. This knowledge is a starting point in order to identify new and specific resistance genes by detecting similar expression patterns. Here we evaluate the usefulness of clustering and data-mining methods to group together known plant resistance genes based on expression profiles. We conduct clustering separately on
P.infestans
inoculated and not-inoculated tomatoes and conclude that conducting the analysis separately is important for each condition, because grouping is different reflecting a characteristic behavior of resistance genes in presence of the pathogen.