A New Constraint-Based Compound Graph Layout Algorithm for Drawing Biochemical Networks

Abstract

Due to the huge amount of information available in biochemical databases, biologists need sophisticated tools to accurately extract the information from such databases and to interpret it correctly. Those tools must be able to dynamically generate any kind of biochemical subgraph (i.e., metabolic pathways, genetic regulation, signal transduction, etc.) in a single graph. The visualization tools must be able to cope with such graphs and to take into account the particular semantics of all kinds of biochemical subgraphs. Therefore, such tools need generic graph layout algorithms that adapt their behavior to the data semantics. In this paper we present the Constrained Compound Graph Layout (C2GL) algorithm designed for the generic representation of biochemical graphs and in which users can represent knowledge about how to draw graphs in accordance with the biochemical semantics. We show how we implemented the C2GL algorithm in the Visual BioMaze framework, the visualization tool of the BioMaze project.