Graph Visualization and Layout

As graphical user interfaces have improved, and more state-of-the-art software tools have incorporated visual functions, interactive graph editing and diagramming facilities have become important components in visualization systems.

Effective analysis of the underlying data in graph visualization is only possible via sound automatic layout capabilities of such systems.

Pathway Layout

Previous version of our tool has featured a new, elegant algorithm for layout of biological signaling pathways [1]. This algorithm uses a force-directed layout scheme, taking into account directional and regional constraints enforced by different molecular interaction types and subcellular locations in a cell. Same pathway is shown with a random layout and after our algorithm is applied in Figure 1.

Figure 1. A randomly laid out p53 pathway in PATIKA version 1.0 (left); same pathway after our layout algorithm executes (right).

Compound Pathway Layout

Pathway drawings in the new generation of PATIKA tools (e.g., PATIKAweb) are even more complicated with nesting / grouping support as PATIKAweb supports advanced features of the PATIKA ontology including molecular complexes and various types of abstractions to represent relational data at varying levels of detail. We have developed a new algorithm for automatically laying out pathway drawings in PATIKAweb [2]. PATIKAweb supports automatic layout of nested pathway drawings (Figure 2).

Figure 2. Sample layouts produced by PATIKAweb's new compound pathway layout algorithm.

This algorithm may be easily adapted to be used in other applications with similar conventions and constraints as well.


[1] B. Genc and U. Dogrusoz, "A Layout Algorithm for Signaling Pathways", Information Sciences, vol. 176, pp. 135-149, 2006.

[2] U. Dogrusoz, E. Giral, A. Cetintas, A. Civril, and E. Demir, "A Compound Graph Layout Algorithm for Biological Pathways", Lecture Notes in Computer Science, vol. 3383, pp. 442-447, 2005.