Semantic visualization of biochemical databases

Abstract

Extracting and visualizing information from biochemical databases is one of the most important challenges in biochemical research. The huge quantity and high complexity of the data available force the biologist to use sophisticated tools for extracting and interpreting accurately the information extracted from the database. These tools must define a graphical semantics associated to the data semantics in accordance with biologist usages. The aim of these tools is to display complex biochemical networks in a readable and understandable way. In this paper we define the notion of customizable representation model, which allows the biologist to change the graphical semantics associated to the data semantics. The approach is also generic since our graphical semantics is common to several kinds of biochemical networks. We also defined adaptive graph layout algorithms taking into account the particular semantics of biochemical networks. We show how we implemented these notions in the BioMaze project 1. © IFIP International Federation for Information Processing 2004.