Inference of protein kinetics by stochastic modeling and simulation of fluorescence recovery after photobleaching experiments

• DOI: 10.1093/bioinformatics/btu619
• Publication Date: 2014-10-02T06:07:10Z
• Authors: Maria Anna Rapsom...; Eugenio Cinquemani; Nickolaos Nikifor...; Panagiotis Kotsantis; John Lygeros; Zoi Lygerou
• Keywords: Identifiability; Photobleaching; Stochastic simulation

Fluorescence recovery after photobleaching (FRAP) is a functional live cell imaging technique that permits the exploration of protein dynamics in living cells. To extract kinetic parameters from FRAP data, number analytical models have been developed. Simplifications are inherent these models, which may lead to inexhaustive or inaccurate exploitation experimental data. An appealing alternative offered by simulation biological processes realistic environments at particle level. However, inference using simulation-based still limited.We introduce and demonstrate new method for parameter values A small silico experiments used construct mapping curves underlying kinetics. Parameter estimates data can then be computed applying observed curves. bootstrap process investigate identifiability physical determine confidence regions their estimates. Our circumvents computational burden seeking best-fitting via iterative simulation. After validation on synthetic applied analysis nuclear proteins Cdt1, PCNA GFPnls. estimation results several samples accordance with previous findings, but also allow us discuss issues as well cell-to-cell variability kinetics.All methods were implemented MATLAB R2011b. Monte Carlo simulations run HPC cluster Brutus ETH [e-mail] [e-mail] available Bioinformatics online.