UNLABELLED: Understanding the relationships between pathways and the altered expression of their components in disease conditions can be addressed in a visual data analysis process. Caleydo uses novel visualization techniques to support life science experts in their analysis of gene expression data in the context of pathways and functions of individual genes. Pathways and gene expression visualizations are placed in a 3D scene where selected entities (i.e. genes) are visually connected. This allows Caleydo to seamlessly integrate interactive gene expression visualization with cross-database pathway exploration. AVAILABILITY: The Caleydo visualization framework is freely available on www.caleydo.org for non-commercial use. It runs on Windows and Linux and requires a 3D capable graphics card.

Abstract Visualizing pathways, i. e. models of cellular functional networks, is a challenging task in computer assisted biomedicine. Pathways are represented as large collections of interwoven graphs, with complex structures present in both the individual graphs and their interconnections. This situation requires the development of novel visualization techniques to allow efficient visual exploration. We present the Caleydo framework, which incorporates a number of approaches to handle such pathways. Navigation in the network of pathways is facilitated by a hierarchical approach which dynamically selects a working set of individual pathways for closer inspection. These pathways are interactively rendered together with visual interconnections in a 2.5D view using graphics hardware acceleration. The layout of individual graphs is not computed automatically, but taken from the KEGG and BioCarta databases, which use layouts that life scientists are familiar with. Therefore they encode essential meta‐information. While the KEGG and BioCarta pathways use a pre‐defined layout, interactions such as linking+brushing, neighborhood search or detail on demand are still fully interactive in Caleydo. We have evaluated Caleydo with pathologists working on the determination of unknown gene functions. Informal experiences confirm that Caleydo is useful in both generating and validating such hypotheses. Even though the presented techniques are applied to medical pathways, the proposed way of interaction is not limited to cellular processes and therefore has the potential to open new possibilities in other fields of application.

Data ow graphs are a very successful paradigm in scientific visualization, while scene graphs are a leading approach in interactive graphics and virtual reality. Both approaches have their distinct advantages, and both build on a common set of basic techniques based on graph data structures. However, despite these similarities, no unified implementation of the two paradigms exists. This paper presents an in-depth analysis of the architectural components of dataflow visualization and scene graphs, and derives a design that integrates both these approaches.The implementation of this design builds on a common software infrastructure based on a scene graph, and extends it with virtualized dataflow, which allows the use of the scene graph structure and traversal mechanism for dynamically building and evaluating dataflow.