Metabolic pathways describe the composition, decomposition, and transformation of metabolites (molecules) via chemical reactions. These pathways have been composed by biologists as road maps that aid them in understanding cell metabolism, which is necessary to determine the orgin–and subsequently the cure for–various kinds of disease.

Merging all pathways results in a Metabolic Network that describes all metabolites and their reactions in an organism. Biologists prefer the reason with metabolic pathways because they are simple, targeted sections of Metabolic networks that usually contain the right quantity of information. However, sometimes interesting events span multiple pathways. In this case a biologist wants to stitch together pathways, creating bigger pathways. Currently this is being done in a manual, time consuming manner.

The aim of this project is to devise and implement techniques that enable biologists to interactively merge and split pathways in a semi-automated manner.

• Extracting pathways from databases such as KEGG and MetaCyc and generating tidy layouts for them (these are not always provided). This includes detecting reaction chains and cycles to emphasize pathway topology.
• Merging (and splitting) existing pathway layouts such that the original layouts are preserved as much as possible, keeping them recognizable as a unit, but also maintaining a tidy global layout.
• Studying the impact of different visualization and animation techniques with respect to these pathway transformations.