The complex mechanisms of the internal operation of cellular functions have not been fully resolved and these functions are regulated by multiple effects, such as transcription regulation, signal transduction, and enzyme catalysis, forming complex interactive mechanisms. This makes the construction of a whole-cell computational model, containing various complex cellular functions, very challenging. However, biological models have played a significant role in the field of systems biology, such as guiding gene-target mining and studying cell metabolic characteristics. Therefore, there is increasing research interest in the construction of whole-cell computational models. Combining two classical languages of systems biology, this review expounds on the development and challenges of whole-cell computational modeling from the two classical methods of steady-state and dynamic modeling. Finally, we propose a new approach for constructing whole-cell computational models.