We describe the construction and analysis of a genome-scale metabolic model of Arabidopsis thaliana primarily derived from the annotations in the Aracyc database. We used techniques based on Linear Programming to demonstrate that: 1) the model is capable of producing biomass components (amino-acids, nucleotides, lipid, starch and cellulose) in the proportion observed experimentally in a heterotrophic suspension culture ; 2) That, approximately, only 15 % of the available reactions are needed for this purpose and that the size of this network is comparable to estimates of minimal network size for other organisms ; 3) That reactions may be grouped according to the changes in flux resulting from a hypothetical stimulus (in this case demand for ATP), and that this allows the identification of potential metabolic modules ; 4) That total ATP demand for growth and maintenance can be inferred, and that this is consistent with previous estimates in prokaryotes and yeast.