Plant Genomics

The complexity and temporal as well as spatial resolution of transcriptome datasets is constantly
increasing due to extensive technological developments. Herewe present methods
for advanced visualization and intuitive exploration of transcriptomics data as necessary prerequisites
in order to facilitate the gain of biological knowledge. Color-coding of structural
images based on the expression level enables a fast visual data analysis in the background
of the examined biological system. The network-based exploration of these visualizations
allows for comparative analysis of genes with specific transcript patterns and supports
the extraction of functional relationships even from large datasets. In order to illustrate the
presented methods, the tool HIVEwas applied for visualization and exploration of databaseretrieved
expression data for master regulators of Arabidopsis thaliana flower and seed
development in the context of corresponding tissue-specific regulatory networks.