SignificanceTo understand developmental patterning of an organism, it is necessary to accurately measure how the state of a gene regulatory network is changing over time. One way of extracting dynamics of a network involves simultaneously imaging several reporters within fixed tissue. Reconstructing dynamics from such data requires staging many samples over time and often leads to low temporal resolution. Time-lapse microscopy of fluorescent transcriptional reporters has revolutionized studies of biological dynamics at the single-cell level. However, this method is limited by the number of reporters that can be imaged at one time. We present a computational method for addressing this problem and demonstrate its application by modeling the gene regulatory network underlying Drosophila posterior patterning and reconstructing its developmental dynamics.
