Getting poster data...
Andreas Maunz, Moritz Gilsdorf, Sebastien Fournier, Christian Blumenröhr, Ralf Horstmöller, Jörg Schmiedle (Hoffmann-La Roche AG Innovation Center Basel, Switzerland)In human or animal cell cultures, cells are perturbed upon certain conditions, and effects are measured on the gene expression level. For example, cells are treated with a compound, then a sample is obtained and mRNA expression is measured. This is done repeatedly under different conditions and a gene interaction network is inferred from the data. The Hive Plot (proposed by Krzywinski in 2011) improves the display of network data over existing layouts in terms of reproducibility and comparability. It assigns nodes (genes) to axes and for each gene chooses a position on the given axis. It therefore enables a visual trade-off between two (graph theoretic or biological) measures. Our integrated analysis platform based on Spotfire and an interactive, D3.js-based Hive Plot implementation allows researchers to identify influential genes visually, complementary to their established methods. The Hive Plot is only one component of our Scientific Visualization Library, providing innovative analysis widgets that can be plugged in a web page and allow interactive visualization of internal and external data to support scientists in their decision-making process.