The complexity and temporal as well as spatial resolution of transcriptome datasets is constantly increasing due to extensive technological developments.Here we present methods for advanced visualization and intuitive exploration of transcriptomics data as necessary surface awaken protein mousse 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 pitchy delight onee stick from large datasets.
In order to illustrate the presented methods, the tool HIVE was applied for visualization and exploration of database-retrieved expression data for master regulators of Arabidopsis thaliana flower and seed development in the context of corresponding tissue-specific regulatory networks.