Significance To 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… Click to show full abstract
Significance To 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.
               
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