Factor Analysis, a multivariate technique for determining the major trends or factors in a data matrix, is shown in this paper to be appropriate for resolving biochemical reaction networks. As opposed to an algorithmic approach, the methods presented in this article are intended to be a highly interactive set of tools. The researcher can use these tools to investigate a data matrix of concentration-change measurements by proposing different reaction networks. Several tools are adapted from other fields, and a few new techniques are proposed. The new techniques involve the estimation (or extraction) of reaction stoichiometries and reaction extents when all the reactions are not present at all times. This article presents theoretical elements, simulation results as well as an application of the method to experimental data from the fed-batch production of Baker’s yeast grown on glucose. Reaction stoichiometries and reaction extents are estimated for the reactions of glucose fermentation, glucose oxidation and ethanol oxidation.