Integrative Approach to Extract the Single-cell Dynamics of LPS-induced $ ext{NF}kappamathrm{B}$ Signal Pathway through Flow Cytometry Measurements and Parameter Estimation Conference Paper uri icon

abstract

  • © 2018 AACC. It is well established that the dynamics of signaling and gene expression in a clonal population of cells vary both in the absence and presence of stimuli. In order to elucidate the stochasticity in signaling and downstream cellular responses, we have formulated a mathematical model and utilized it along with single-cell experimental measurements to investigate the cell-to-cell variability in the response of mouse macrophages to lipopolysaccharide (LPS). Since the single-cell mathematical model is computationally expensive to simulate, a semi-stochastic model that combines a deterministic model with parameters that have distributions at the single-cell level is more viable than a stochastic model. This modeling approach requires an accurate deterministic model a priori. Motivated by above considerations, this work aimed to quantitatively calibrate the deterministic model that can simulate the average single-cell dynamics via a systematic approach, which combines single-cell experimental measurements and a parameter selection method, with the LPS-induced NFκ B signal pathway as an example case.

author list (cited authors)

  • Lee, D., Ding, Y., Jayaraman, A., & Kwon, J.

publication date

  • January 1, 2018 11:11 AM

publisher