It is essential to understand the biology at the system level since an organism can be viewed as a network of interactions among genes, proteins and biochemical reactions which give rise to life. This work focuses on developing systems biology approaches, which advocate in system-level understanding, for studying transcriptional regulation, metabolic control, and the microbial competition for growth. In studying transcriptional regulation, Network Component Analysis (NCA) was developed to determine the activities and key target genes of transcription factors (TFs) from gene expression and TF-gene interaction information. The TF activity information derived from NCA would be particularly useful for looking at the effects of drugs or environmental switch. The theoretical and numerical issues of the method were discussed in this work. The approach was applied for identifying the TFs and signaling pathways regulated by PTEN, a tumor suppressor protein, in different human cancers and animal models. Besides studying transcription regulation, this work also focuses on modeling the metabolic network, which will in turn help to identify the enzymes controlling the metabolic flux. Complete modeling of metabolic networks is often a challenge because of the lack of kinetics. As a step towards this goal, the ensemble modeling approach was developed to build an ensemble of dynamic models reach the same steady state. This ensemble allowed for the examination of possible phenotypes of the network upon perturbations, such as changes in enzyme expression levels, and identification of the rate controlling hotspots in several metabolic systems. Finally this work seeks to determine the underlying principles of microbial competition for growth. The least action principle and its Euler-Lagrangian theorem were used for exploring the dynamics of microbial growth, and derived a conserved quantity, named bio-Hamiltonian, involving biological activities. It was shown that through competition, microbes would be selected to take the least "action" in growth by stabilizing proteins and by achieving a balanced growth for intracellular components.