Data mining and influential analysis of gene expression data for plant resistance genes identification in tomato (Solanum lycopersicum)
Abstract
Results: Here, we evaluate the usefulness of clustering, data-mining and regression to identify potential new resistance genes. Three types of analyses were conducted separately over two conditions, tomatoes inoculated with Phytophtora infestans and not inoculated tomatoes. Predictions for 10 new resistance genes obtained by all applied methods were selected as being the most reliable and are therefore reported as potential resistance genes.
Conclusion: Application of different statistical analysis to detect potential resistance genes reliably have shown to conduct to interesting results that improve knowledge on molecular mechanisms of plant resistance to pathogens.