Journal of Chemical Information & Computer Sciences
CHI '94 Conference Companion on Human Factors in Computing Systems
Drawing graphs
Graph Drawing: Algorithms for the Visualization of Graphs
Graph Drawing: Algorithms for the Visualization of Graphs
A Technique for Drawing Directed Graphs
IEEE Transactions on Software Engineering
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Systems Biology: Properties of Reconstructed Networks
Systems Biology: Properties of Reconstructed Networks
Dynamic exploration and editing of KEGG pathway diagrams
Bioinformatics
IEEE Transactions on Visualization and Computer Graphics
Functional Evolution of Ribozyme-Catalyzed Metabolisms in a Graph-Based Toy-Universe
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
Human-centered visualization environments
Human-centered visualization environments
A sequence-to-function map for ribozyme-catalyzed metabolisms
ECAL'09 Proceedings of the 10th European conference on Advances in artificial life: Darwin meets von Neumann - Volume Part II
On open problems in biological network visualization
GD'09 Proceedings of the 17th international conference on Graph Drawing
A novel grid-based visualization approach for metabolic networks with advanced focus&context view
GD'09 Proceedings of the 17th international conference on Graph Drawing
Preserving the mental map using foresighted layout
EGVISSYM'01 Proceedings of the 3rd Joint Eurographics - IEEE TCVG conference on Visualization
In silica evolution of early metabolism
Artificial Life
Toward the role of interaction in visual analytics
Proceedings of the Winter Simulation Conference
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We extend our previous work on the exploration of static metabolic networks to evolving, and therefore dynamic, pathways. We apply our visualization software to data from a simulation of early metabolism. Thereby, we show that our technique allows us to test and argue for or against different scenarios for the evolution of metabolic pathways. This supports a profound and efficient analysis of the structure and properties of the generated metabolic networks and its underlying components, while giving the user a vivid impression of the dynamics of the system. The analysis process is inspired by Ben Shneiderman's mantra of information visualization. For the overview, user-defined diagrams give insight into topological changes of the graph as well as changes in the attribute set associated with the participating enzymes, substances and reactions. This way, "interesting features" in time as well as in space can be recognized. A linked view implementation enables the navigation into more detailed layers of perspective for in-depth analysis of individual network configurations.