Abstract
Predicting transcriptional dynamics of cells provides valuable insight into complex subcellular responses which lead to broad signaling pathways that dictate cellular phenotypic behavior. Understanding the transcriptional dynamics of certain genes is imperative in predicting cellular phenotypes and the behavior of cells experiencing dysregulation from environmental stresses. For this reason, we construct a computational framework that uses the output of single molecule in situ hybridization (smFISH), which supplies us with snapshots of RNA levels amongst the population of cells at different points in time, to accurately deduce the underlying gene network models.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
