The functions of living cells are regulated by the complex biochemical network, which consists of stochastic interactions among genes and proteins. However, due to the complexity of biochemical networks and the limit of experimental techniques, identifying entire biochemical interaction network is still far from complete. On the other hand, output of the networks, timecourses of genes and proteins can be easily acquired with advances in technology. I will describe how to reveal the biochemical network architecture with oscillating timecourse data. Next, I will discuss how to reduce or simplify the stochastic biochemical networks while preserving the slow timescale dynamics. Specifically, I will show when macroscopic rate functions (e.g. Hill functions) describing the slow timescale dynamics of deterministic systems can be used for stochastic simulations. Finally, I will discuss the role of network topology in determining its function and dynamics with an example of circadian clock.