Layered networks in 3D
The basic idea of Arena3D is to use multilayered graphs to visualize biological networks. In such a way heterogeneous data will be distinguished between each other.
- Multilayered graphs
- Different layout algorithms
- Compatibility with other tools
- Clustering—Kmeans , Affinity Propagation, MCL
- Clustering—HCL, NJ, UPGMA
- Easy navigation and searching
- Clustering between layers
- Indirect connections
- Pre-defined clustering
- Save and reload network
Arena3D is free for academic users. Commercial users please contact us at rschneid'at'embl.de.
EMBL all rights reserved.
What's new in v2.0
Visualizing temporal patterns in biological systems
The aim is to integrate information obtained from various experiments that deal with time lapse data (RNA interference, microarrays etc.) in a visually comprehensive framework that enables the capturing of crucial time points of biological processes, as well as a visualization of dynamic motifs and similarities between entities at different levels, as a way of pinpointing hotspots of biosystem robustness and triggering the generation of new hypotheses. Temporal patterns of different events/processes will be identified and analyzed.
Examples are shown below, with application to a dataset of siRNA knockdown results for targeted genes essential for the cell cycle, detecting the temporal succession of phenotypic events, as described in  (http://www.mitocheck.org/). Different phenotypes are visualized on different layers and the nodes represent individual gene knockdown events.
Neumann et al. Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes. Nature, 464:721-727, 2010.
Here are some of the new features of Arena3D:
- visualizing changes in gene expression through animated changes in node color
- clustering on different layers according to highest expression changes
- highlighting the genes with highest impact at consecutive time points
- individual gene tracking
- linking correlated genes
- coloring according to gene pattern similarity
- line plots of expression time course on node click events
- colorblind-safe gradients
The above functionality is applicable to any type of time course data, not restricted to expression data.
Dynamic changes in the system are tracked through changes in node color, clustering on different layers and individual gene tracking. Correlations between genes can be displayed.
Coloring genes according to some similarity score is enabled.