Flavonoids are plant secondary metabolites that are extensively studied for their proposed positive effects on human health. They are the end products of a cascade of enzymatic reactions that convert initially toxic substances to glycosylated forms. To determine which enzymes are precisely responsible for which conversions is by far not trivial, since hundreds of candidate genes are in principle capable of performing the transformation of interest. In this paper we propose a method to solve this problem for the glycosylation of flavonoids by coupling gene expression data to the metabolic pathway underlying glycosylation. The core of the method is to estimate time dependent
coefficients in a highly efficient way. To show how this approach performs, we apply this method to study the flavonoid glycosylation pathway in tomato (Solanum lycopersicum) seedlings.
|Title of host publication||Proceedings of the International Workshop on Computational Systems Biology , 4-6 June 2012, Ulm, Germany|
|Publisher||Tampere International Center for Signal Processing|
|Publication status||Published - 2012|