Although live cell imaging has not been often used in the study of gene regulatory networks, it is a method that uniquely enables the measurement of dynamic events in single cells. Dynamical information about network components and their interactions is critical to predictive modeling of gene regulatory networks, and is currently not accessible through omics and other end point techniques. In this brief review we discuss the importance of dynamics to network modeling, and recent advances in imaging and genetic engineering technologies that are making the use of imaging for network analysis possible.
Computational and Structural Biotechnology Journal
systems biology, live cell imaging, gene regulatory networks, Langevin equation