The very first research project that I focused on during my undergrad was to improve the model for estimating fluorophore diffusivity in FRAP experiments. FRAP is short for fluorescence recovery after photobleaching, which is an useful method for quantifying two-dimensional lateral diffusion through a fluorescently labelled thin film. Back then, the lipid bilayer platforms most commonly used in our lab include the ones composed of DOPC (a kind of phospholipid), DOPC with GPMVs (giant plasma membrane vesicles), or GPMVs. While the pre-existing MATLAB code in our lab was able to fit the recovery curve obtained from FRAP conducted on DOPC platforms with decent quality ($R^2\approx0.95$), its fitting quality was lower for the other two platforms ($R^2$ ranging from 0.75 to 0.90). To better model the recovery curve and accurately estimate the fluorophore diffusivity on different membrane systems, I refactored the MATLAB code by improving the numerical methods for approximating the solution of the governing diffusion equation. I also added various functionalities to the code for data visualization (see Figure 1) and additional analysis. As a result, the $R^2$ value was substantially improved to at least 0.97 for all three kinds of membrane systems.
For more details about the model derivation and code implementation, please check the video (in Mandarin) or the slides (in English) for this project.
Wei-Tse Hsu
Postdoctoral Research Associate in Drug Design
Computational Biophysicist keen on molecular dynamics, deep learning, and education