The main focus of this thesis is the development oftechniques to aid in the process of inferring howgenes interact with each other in a living organism.Knowledge of these interactions have implications ingaining an understanding of how cellular processeswork, how organisms survive and evolve underdifferent environmental conditions. The techniques are based on an S-system type differential equationmodel for the process of gene regulation. They aredesigned to handle data arising from experimentalsetups like DNA microarrays. Methods to handle datacollected under both steady state and time-varyingmanner are developed. They were validated using bothsimulated data and also data from real organisms. Thedata used were steady state data from the set ofgenes involved in the SOS response of E.Coli andtime-varying data from a subset of genes involved inthe formation of the endospore in the Bacillusanthracis. The techniques proposed have advantagesover the current methods used in that they not onlycapture the inherent non-linearity of the process butalso account for the regulatory behavior of proteinsand handle data directly from DNA microarray experiments.