Representing experimental biological data in metabolic networks

This paper describes a novel approach to representing experimental biological data in metabolic networks. The aim is to allow biologists to visualise and analyse the data in the context of the underlying processes. Biological networks can be modelled as graphs and visualised using graph drawing methods. We present a general method for mapping experimental data onto nodes and edges of a graph and to visualise the data-enriched networks in 2 dimensions such that the data is easy to understand. Our focus is on time series data occurring during developmental analysis. We demonstrate the utility of our approach by a real world example from the seed development of barley (Hordeum vulgare)